The Emperor's New Mind

The Emperor's New Mind

The Emperor's New Mind: Concerning Computers, Minds and The Laws of Physics is a 1989 book by the mathematical physicist Roger Penrose that posits a quantum mind theory. Penrose argues that human consciousness is non-algorithmic, and thus is not capable of being modeled by a conventional Turing machine, which includes a digital computer. Penrose hypothesizes that quantum mechanics plays an essential role in the understanding of human consciousness. The collapse of the quantum wavefunction is seen as playing an important role in brain function. Most of the book is spent reviewing, for the scientifically-minded lay-reader, a plethora of interrelated subjects such as Newtonian physics, special and general relativity, the philosophy and limitations of mathematics, quantum physics, cosmology, and the nature of time. Penrose intermittently describes how each of these bears on his developing theme: that consciousness is not "algorithmic". Only the later portions of the book address the thesis directly. == Overview == Penrose states that his ideas on the nature of consciousness are speculative, and his thesis is considered erroneous by some experts in the fields of philosophy, computer science, and robotics. The Emperor's New Mind attacks the claims of artificial intelligence using the physics of computing: Penrose notes that the present home of computing lies more in the tangible world of classical mechanics than in the imponderable realm of quantum mechanics. The modern computer is a deterministic system that for the most part simply executes algorithms. Penrose shows that, by reconfiguring the boundaries of a billiard table, one might make a computer in which the billiard balls act as message carriers and their interactions act as logical decisions. The billiard-ball computer was first designed some years ago by Edward Fredkin and Tommaso Toffoli of the Massachusetts Institute of Technology. == Reception == Following the publication of the book, Penrose began to collaborate with Stuart Hameroff on a biological analog to quantum computation involving microtubules, which became the foundation for his subsequent book, Shadows of the Mind: A Search for the Missing Science of Consciousness. Penrose won the Science Book Prize in 1990 for The Emperor's New Mind. According to an article in the American Journal of Physics, Penrose incorrectly claims a barrier far away from a localized particle can affect the particle.

Joint constraints

Joint constraints are rotational constraints on the joints of an artificial system. They are used in an inverse kinematics chain, in fields including 3D animation or robotics. Joint constraints can be implemented in a number of ways, but the most common method is to limit rotation about the X, Y and Z axis independently. An elbow, for instance, could be represented by limiting rotation on X and Z axis to 0 degrees, and constraining the Y-axis rotation to 130 degrees. To simulate joint constraints more accurately, dot-products can be used with an independent axis to repulse the child bones orientation from the unreachable axis. Limiting the orientation of the child bone to a border of vectors tangent to the surface of the joint, repulsing the child bone away from the border, can also be useful in the precise restriction of shoulder movement.

Open Mashup Alliance

The Open Mashup Alliance (OMA) is a non-profit consortium that promotes the adoption of mashup solutions in the enterprise through the evolution of enterprise mashup standards like EMML. The initial members of the OMA include some large technology companies such as Adobe Systems, Hewlett-Packard, and Intel and some major technology users such as Bank of America and Capgemini. According to Dion Hinchcliffe, "Ultimately, the OMA creates a standardized approach to enterprise mashups that creates an open and vibrant market for competing runtimes, mashups, and an array of important aftermarket services such as development/testing tools, management and administration appliances, governance frameworks, education, professional services, and so on." == Specification development == The initial focus of the OMA is developing EMML, which is a declarative mashup domain-specific language (DSL) aimed at creating enterprise mashups. The EMML language provides a comprehensive set of high-level mashup-domain vocabulary to consume and mash a variety of web data sources. EMML provides a uniform syntax to invoke heterogeneous service styles: REST, WSDL, RSS/ATOM, RDBMS, and POJO. EMML also provides the ability to mix and match diverse data formats: XML, JSON, JDBC, JavaObjects, and primitive types. The OMA website provides the EMML specification, the EMML schema, a reference runtime implementation capable of running EMML scripts, sample EMML mashup scripts, and technical documentation. The OMA is developing EMML under a Creative Commons Attribution No Derivatives license. The eventual objective of the OMA is to submit the EMML specification and any other OMA specifications to a recognized industry standards body.

Pull technology

Pull coding or client pull is a style of network communication, where the initial request for data originates from the client, and then is responded to by the server. The reverse is known as push technology, where the server pushes data to clients. Pull requests form the foundation of network computing, where many clients request data from centralized servers. Pull is used extensively on the Internet for HTTP page requests from websites. A push can also be simulated using multiple pulls within a short amount of time. For example, when pulling POP3 email messages from a server, a client can make regular pull requests, every few minutes. To the user, the email then appears to be pushed, as emails appear to arrive close to real-time. A trade-off of this system is that it places a heavier load on both the server and network to function correctly. Many web feeds, such as RSS are technically pulled by the client. With RSS, the user's RSS reader polls the server periodically for new content; the server does not send information to the client unrequested. This continual polling is inefficient and has contributed to the shutdown or reduction of several popular RSS feeds that could not handle the bandwidth. For solving this problem, the WebSub protocol, as another example of a push code, was devised. Podcasting is specifically a pull technology. When a new podcast episode is published to an RSS feed, it sits on the server until it is requested by a feed reader, mobile podcasting app, or directory. Directories such as Apple Podcasts (iTunes), The Blubrry Directory, and many apps' directories request the RSS feed periodically to update the Podcast's listing on those platforms. Subscribers to those RSS feeds via app or reader will get the episodes when they request the RSS feed next time, independent of when the directory listing updates.

G7 Rapid Response Mechanism

The G7 Rapid Response Mechanism (RRM) is an initiative introduced in the "Charlevoix Commitment on Defending Democracy from Foreign Threats", issued by the leaders of the Group of Seven (G7) countries—United States, Canada, Japan, United Kingdom, France, Germany and Italy—on June 9, 2018, during their summit in Charlevoix, Quebec. The RRM's mandate is to strengthen the coordination of G7 member countries, as well as "to identify and respond to diverse and evolving threats to our democracies, including through sharing information and analysis, and identifying opportunities for coordinated response" The G7 is an informal international intergovernmental economic organization that meets annually, whose members represent the seven wealthiest advanced economies in the world, as measured by the International Monetary Fund (IMF). == Constituents == The following countries and organisations are members and observers (associate members) of the G7 Rapid Response Mechanism: Australia Canada France Germany Italy Japan Netherlands New Zealand Poland Sweden United Kingdom United States European Union North Atlantic Treaty Organization == Mandate == The RRM was mandated to "strengthen coordination to prevent, thwart and respond to malign and evolving threats to G7 democracies." It "will share information and threat analysis related to various threats to democracy, and is an established mechanism to identify opportunities for coordinated response." According to the Institute for Research on Public Policy's Policy Options magazine, the "RRM initiative seeks to strengthen the leading democracies' coordination to identify and respond to diverse and evolving threats…including through sharing information and analysis, and identifying opportunities for a coordinated response." == Administration == The RRM initiative is led by Canada through Global Affairs Canada's Centre for International Digital Policy. Tara Denham, Director of the Centre for International Digital Policy at Global Affairs Canada, directed the team responsible for setting up the RRM Coordination Unit. Global Affairs Canada—the Department of Foreign Affairs, Trade and Development—is the federal Canadian ministry responsible for diplomatic and consular relations, international trade, and international development and humanitarian assistance. The Centre for International Digital Policy includes the Digital Inclusion Lab and the RRM. Denham is also the RRM's Canadian Focal Point. At a briefing on "the security and intelligence threats to elections" of the House of Commons Standing Committee on Access to Information, Privacy and Ethics, the chair Bob Zimmer (CPC), said that the 2019 general election "may be different" from past elections in Canada. as the "tools that were used to strengthen civic engagement are being used to undermine, disrupt and destabilize democracy." "Democracies around the world have entered a new era—an era of heightened threat and heightened vigilance—and 2019 will see a number of countries brace for volleys of attempted disruption: India, Australia, Ukraine, Switzerland, Belgium, the EU and, of course, Canada. Evidence has confirmed that the most recent Canadian general election, in 2015, was unencumbered by interference, although there were some relatively primitive attempts to disrupt, misinform and divide. These efforts were few in number and uncoordinated, and had no visible impact on the voter, either online or in line." Zimmer described the initiative's three pillars. "enhancing citizen preparedness" through the "digital citizen initiative" "improving organizational readiness" with national security and intelligence agencies supporting Elections Canada "ensure a comprehensive understanding of and response to any threats to Canada's democratic process." by establishing the Security and Intelligence Threats to Elections Task Force (SITE) which works as a team with the Communications Security Establishment (CSE), the Canadian Security Intelligence Service (CSIS), the Royal Canadian Mounted Police (RCMP), as well as Global Affairs Canada Zimmer said that as part of the third pillar, "We have activated the G7 rapid response mechanism, announced at the G7 leaders' summit in Charlevoix, to strengthen coordination among our G7 allies and to ensure that there is international collaboration and coordination in responding to foreign threats to democracy." == Background == === Charlevoix summit === The G7 met from June 8 to 9, 2018 during their summit at the Manoir Richelieu in Charlevoix, in La Malbaie, Quebec. The Charlevoix Summit was the 44th G7 summit. The group issued eight "Commitments" at the summit. They included: Commitment on Defending Democracy from Foreign Threats Commitment on Equality and Economic Growth Commitment to End Sexual and Gender-Based Violence, Abuse and Harassment in Digital Contexts Declaration on Quality Education for Girls, Adolescent Girls and Women in Developing Countries Commitment on Innovative Financing for Development. Prime Minister Justin Trudeau announced five themes for Canada's G7 presidency which began in January 2018. === Defending Democracy from Foreign Threats === "We commit to take concerted action in responding to foreign actors who seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security as outlined in the Charlevoix Commitment on Defending Democracy from Foreign Threats. We recognize that such threats, particularly those originating from state actors, are not just threats to G7 nations, but to international peace and security and the rules-based international order. We call on others to join us in addressing these growing threats by increasing the resilience and security of our institutions, economies and societies, and by taking concerted action to identify and hold to account those who would do us harm." They committed to "cooperate in defending democracies from foreign threats and establish a response mechanism for that purpose". "Democracy and the rules-based international order are increasingly being challenged by authoritarianism and the defiance of international norms. In particular, foreign actors seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security. These malicious, multi-faceted and ever-evolving tactics constitute a serious strategic threat which we commit to confront together, working with other governments that share our democratic values." The Charlevoix Commitment states that "foreign actors seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security. These malicious, multi-faceted and ever-evolving tactics constitute a serious strategic threat which we commit to confront together, working together with other governments that share our democratic values." The Charlevoix Summit resolved to "establish a G7 Rapid Response Mechanism to strengthen our coordination to identify and respond to diverse and evolving threats to our democracies, including through sharing information and analysis, and identifying opportunities for coordinated response." == Monitored elections == === 2019 European Parliament election === RRM Canada's comprehensive report on the 2019 European Parliament election analyzed open data "related to foreign interference during and leading up to the 2019 European Union Parliamentary Elections, May 23–26, 2019". RRM Canada did not find "significant evidence of state-based foreign interference, or any large-scale, organized and coordinated efforts by non-state actors". They did find that "national or international non-state actors" used tactics based on those used by the Russian sponsored Internet Research Agency (IRA) in previous elections, "such as the 2016 U.S. Elections". For example, blogs, webpages, and social media accounts on Twitter, Facebook and Reddit "were used to spread divisive and false information to damage and negatively impact social cohesion and trust in democratic processes and institutions" in coordinated networks of Facebook groups. === 2019 Alberta general election === RRM Canada's analyz report on the 2019 Alberta general election was intended to "identify any emerging tactics in foreign interference and draw lessons learned for the Canadian general elections scheduled to take place in October 2019." No foreign activity was detected, although the data revealed ""suspicious account creation pattern that is indicative of troll or bot activity". They found "automated inauthentic behaviour and trolling activities" but concluded that they were "very likely domestic". The data showed "suspicious account creation pattern that is indicative of troll or bot activity", and "spikes in account creation" which suggested the "presence of accounts developed for a specific purpose." The accounts were very likely domestic and were "mainly comprised of supporters of the United Conservative Party (UCP)." A seco

Text Retrieval Conference

The Text REtrieval Conference (TREC) is an ongoing series of workshops focusing on a list of different information retrieval (IR) research areas, or tracks. It is co-sponsored by the National Institute of Standards and Technology (NIST) and the Intelligence Advanced Research Projects Activity (part of the office of the Director of National Intelligence), and began in 1992 as part of the TIPSTER Text program. Its purpose is to support and encourage research within the information retrieval community by providing the infrastructure necessary for large-scale evaluation of text retrieval methodologies and to increase the speed of lab-to-product transfer of technology. TREC's evaluation protocols have improved many search technologies. A 2010 study estimated that "without TREC, U.S. Internet users would have spent up to 3.15 billion additional hours using web search engines between 1999 and 2009." Hal Varian the Chief Economist at Google wrote that "The TREC data revitalized research on information retrieval. Having a standard, widely available, and carefully constructed set of data laid the groundwork for further innovation in this field." Each track has a challenge wherein NIST provides participating groups with data sets and test problems. Depending on track, test problems might be questions, topics, or target extractable features. Uniform scoring is performed so the systems can be fairly evaluated. After evaluation of the results, a workshop provides a place for participants to collect together thoughts and ideas and present current and future research work.Text Retrieval Conference started in 1992, funded by DARPA (US Defense Advanced Research Project) and run by NIST. Its purpose was to support research within the information retrieval community by providing the infrastructure necessary for large-scale evaluation of text retrieval methodologies. == Goals == Encourage retrieval search based on large text collections Increase communication among industry, academia, and government by creating an open forum for the exchange of research ideas Speed the transfer of technology from research labs into commercial products by demonstrating substantial improvements retrieval methodologies on real world problems To increase the availability of appropriate evaluation techniques for use by industry and academia including development of new evaluation techniques more applicable to current systems TREC is overseen by a program committee consisting of representatives from government, industry, and academia. For each TREC, NIST provide a set of documents and questions. Participants run their own retrieval system on the data and return to NIST a list of retrieved top-ranked documents. NIST pools the individual result judges the retrieved documents for correctness and evaluates the results. The TREC cycle ends with a workshop that is a forum for participants to share their experiences. == Relevance judgments in TREC == TREC defines relevance as: "If you were writing a report on the subject of the topic and would use the information contained in the document in the report, then the document is relevant." Most TREC retrieval tasks use binary relevance: a document is either relevant or not relevant. Some TREC tasks use graded relevance, capturing multiple degrees of relevance. Most TREC collections are too large to perform complete relevance assessment; for these collections it is impossible to calculate the absolute recall for each query. To decide which documents to assess, TREC usually uses a method call pooling. In this method, the top-ranked n documents from each contributing run are aggregated, and the resulting document set is judged completely. == Various TRECs == In 1992 TREC-1 was held at NIST. The first conference attracted 28 groups of researchers from academia and industry. It demonstrated a wide range of different approaches to the retrieval of text from large document collections .Finally TREC1 revealed the facts that automatic construction of queries from natural language query statements seems to work. Techniques based on natural language processing were no better no worse than those based on vector or probabilistic approach. TREC2 Took place in August 1993. 31 group of researchers participated in this. Two types of retrieval were examined. Retrieval using an ‘ad hoc’ query and retrieval using a ‘routing' query In TREC-3 a small group experiments worked with Spanish language collection and others dealt with interactive query formulation in multiple databases TREC-4 they made even shorter to investigate the problems with very short user statements TREC-5 includes both short and long versions of the topics with the goal of carrying out deeper investigation into which types of techniques work well on various lengths of topics In TREC-6 Three new tracks speech, cross language, high precision information retrieval were introduced. The goal of cross language information retrieval is to facilitate research on system that are able to retrieve relevant document regardless of language of the source document TREC-7 contained seven tracks out of which two were new Query track and very large corpus track. The goal of the query track was to create a large query collection TREC-8 contain seven tracks out of which two –question answering and web tracks were new. The objective of QA query is to explore the possibilities of providing answers to specific natural language queries TREC-9 Includes seven tracks In TREC-10 Video tracks introduced Video tracks design to promote research in content based retrieval from digital video In TREC-11 Novelty tracks introduced. The goal of novelty track is to investigate systems abilities to locate relevant and new information within the ranked set of documents returned by a traditional document retrieval system TREC-12 held in 2003 added three new tracks; Genome track, robust retrieval track, HARD (Highly Accurate Retrieval from Documents) == Tracks == === Current tracks === New tracks are added as new research needs are identified, this list is current for TREC 2018. CENTRE Track – Goal: run in parallel CLEF 2018, NTCIR-14, TREC 2018 to develop and tune an IR reproducibility evaluation protocol (new track for 2018). Common Core Track – Goal: an ad hoc search task over news documents. Complex Answer Retrieval (CAR) – Goal: to develop systems capable of answering complex information needs by collating information from an entire corpus. Incident Streams Track – Goal: to research technologies to automatically process social media streams during emergency situations (new track for TREC 2018). The News Track – Goal: partnership with The Washington Post to develop test collections in news environment (new for 2018). Precision Medicine Track – Goal: a specialization of the Clinical Decision Support track to focus on linking oncology patient data to clinical trials. Real-Time Summarization Track (RTS) – Goal: to explore techniques for real-time update summaries from social media streams. === Past tracks === Chemical Track – Goal: to develop and evaluate technology for large scale search in chemistry-related documents, including academic papers and patents, to better meet the needs of professional searchers, and specifically patent searchers and chemists. Clinical Decision Support Track – Goal: to investigate techniques for linking medical cases to information relevant for patient care Contextual Suggestion Track – Goal: to investigate search techniques for complex information needs that are highly dependent on context and user interests. Crowdsourcing Track – Goal: to provide a collaborative venue for exploring crowdsourcing methods both for evaluating search and for performing search tasks. Genomics Track – Goal: to study the retrieval of genomic data, not just gene sequences but also supporting documentation such as research papers, lab reports, etc. Last ran on TREC 2007. Dynamic Domain Track – Goal: to investigate domain-specific search algorithms that adapt to the dynamic information needs of professional users as they explore in complex domains. Enterprise Track – Goal: to study search over the data of an organization to complete some task. Last ran on TREC 2008. Entity Track – Goal: to perform entity-related search on Web data. These search tasks (such as finding entities and properties of entities) address common information needs that are not that well modeled as ad hoc document search. Cross-Language Track – Goal: to investigate the ability of retrieval systems to find documents topically regardless of source language. After 1999, this track spun off into CLEF. FedWeb Track – Goal: to select best resources to forward a query to, and merge the results so that most relevant are on the top. Federated Web Search Track – Goal: to investigate techniques for the selection and combination of search results from a large number of real on-line web search services. Filtering Track – Goal: to binarily decide retrieval of new

Far-Play

Far-Play (stylized fAR-Play, from augmented reality) was a software platform developed at the University of Alberta, for creating location-based, scavenger-hunt style games which use the GPS and web-connectivity features of a player's smartphone. According to the development team, "our long-term objective is to develop a general framework that supports the implementation of AARGs that are fun to play and also educational". It utilizes Layar, an augmented reality smartphone application, QR codes located at particular real-world sites, or a phone's web browser, to facilitate games which require players to be in close physical proximity to predefined "nodes". A node, referred to by the developers as a Virtual Point of Interest (vPOI), is a point in space defined by a set of map coordinates; fAR-Play uses the GPS function of a player's smartphone — or, for indoor games, which are not easily tracked by GPS satellites, specially-created QR codes— to confirm that they are adequately near a given node. Once a player is within a node's proximity, Layar's various augmented reality features can be utilized to display a range of extra content overlaid upon the physical play-space or launch another application for extra functionality. == Development and features == fAR-Play began development in 2008, emerging from a collaborative project undertaken by a group of University of Alberta students from the Computer Science and Humanities Computing departments. fAR-Play is still under development, but a beta version is available for testing by request. fAR-Play's development is managed by a team of interdisciplinary professors and students at the University of Alberta. Currently, the developing team's roster includes Supervising Professors Geoffrey Rockwell and Eleni Stroulia, Developers Lucio Gutierrez and Matthew Delaney, and Website Developers Calen Henry and Garry Wong. === Technology === fAR-Play relies on a number of open- and closed-source web technologies as tools to create, and enhance the users' experience. Layar is the recommended client-side frontend for delivering game content to the player; it is available on Android and iOS, which covers over 91% of smartphones. While Layar is not a requirement to play fAR-Play games, the application does supply additional augmented reality functionality; Layar also includes a built-in QR scanner. Depending on the design of the particular game, the player may instead use a dedicated QR code scanner; the developers recommend BeeTagg, but any such application will do. Layar or a QR code scanner are the maximum software requirements to play a fAR-Play game, making implementation of games on a wide variety of platforms relatively straightforward. fAR-Play games can also be designed for play strictly within a mobile phone's web browser. On the server side, fAR-Play's engine is composed of an Apache server which manages the system's web interface, including the mobile and desktop versions of the fAR-Play website, and a Java-based REST framework for managing the database of nodes. === Features === As a platform for designing AR games, as opposed to an AR game itself, fAR-Play offers little in the way of explicit shapes or patterns for games to take; instead, these elements are left to the game designer or players to develop. However, the nonspecific nature of nodes, the many options they offer for content delivery, and the open design of the platform are such that these elements can be developed extensively. Functionally, fAR-Play is a tool for tracking arbitrary points in space and a given player's proximity to them; what it does beyond that is up to the developers' and players' discretion. However, the fAR-Play website contains a leaderboard which tracks registered user's total scores. Players are assigned levels based on their total score, ranging from Novice — Super Player. Player profiles will display nodes that the player has recently caught, and any achievements the player has gained. Additionally, players can share their adventure progress, achievements, and the capture of vPOIs on Facebook. == How to play == In order to participate in the locative aspects of fAR-Play games, users must have an Android or iOS mobile device and access to wireless internet. Players can participate in fAR-Play anonymously, or create and sign into a fAR-Play account. Those who choose to play anonymously will lose the ability to track their progress across multiple games. When signed in, the player is presented with a list of games that are currently available for play. Each game includes a brief description and the various "adventures" available to the player. Once the game has been started, the player has three different methods for capturing nodes: they may scan a QR in the physical space, discover a node through the Layar camera virtual view, or receive a link in their device's web browser. === QR codes and Layar === QR codes can only be used as a method for capturing nodes and initiating games when there is a physical code present. In order to scan a QR code, players are required to have an application which can capture and recognize QR codes. If the player is utilizing a QR scanning application that has a built in browser, they will be required to log into fAR-Play through the app. Layar is a free to download augmented reality app, containing a built in QR code scanner, which enables its users to participate in fAR-Play games. === Capturing nodes === Layar permits the player to see nodes on their mobile device, guiding the player to their goal. Using this application, the player is able to navigate to their objective with map provided by Google Maps' API or by using their camera — Layar overlays a virtual image onto the real-world scene presented by the camera. The representations on screen expand in size as the player approaches the node destination, simulating relative distance. If the player taps any of the nodes that are presented on the screen, they will be provided additional information about that node, including the node's name and a brief description. Nodes can be captured by tapping the "capture" button. === Playing on browsers === The player can also play fAR-Play games within their mobile device's browser. By visiting https://archive.today/20131123223038/http://farplay.ualberta.ca/far-play/ on a mobile device, players will be presented with a fully realized user interface, permitting full interaction with the games. The player can capture the in game vPOIs through their browser by tapping the "nodes" button. This will bring up a list of all the accessible nodes, complete with a brief description for each location. By clicking on one of the nodes, the player is shown to a screen with a mapped location of the vPOI, an in-depth description of it, and hints. At the top of the page, the player can tap "CAPTURE THIS NODE" and advance in the game. When attempting to capture a node, the developer may or may not associate a challenge with the node. For example, in the game "Zombies ate my Campus", when players are attempting to capture a node, they're presented with a multiple choice question associated with the current node. === Game types === Players complete an adventure when they have captured all of the nodes within it. fAR-Play provides two game modes: in a Virtual Scavenger Hunt, nodes must be captured in a specific order; in a Virtual Treasure Hunt, the order is unimportant. == Existing fAR-Play games == Games currently available through fAR-Play include: Giselle Ever After Thought Hub Comics Arts Capture Challenge Pioneering Edmonton The Intelliphone Challenge A Tour of Atwater Zombies ate my Campus == For developers == fAR-Play's ultimate goal is to provide a simple, effective platform for the creation of locative augmented reality games, but the developer tools are still under active development and not openly available to the public. Access can be granted on a case-by-case basis, however, and a developer's manual is available. Users with development privileges can create new games or edit their existing games, in addition to playing their own or others' games. === Adventures === Games that are developed with fAR-Play are segmented into components called "Adventures". To progress through each game adventure, the player must reach and capture virtual points of interest, referred to in the game as vPOIs. In order to capture a vPOI, the player must travel to a physical location that is set by the developer. It is the developer's choice to include a challenge question to capture the vPOI, though it is not mandatory. A deduction of points can be implemented if the player submits an incorrect answer to a challenge question. === Points and achievements === Each of the nodes will reward the player with a predetermined number of points once they have been captured by the player. These points are added to the player's total points. Each of the adventures that are created require a predetermined number of vPOIs