Game Theory Software

Software Tools for Game Theory

Gambit is an open-source collection of tools for doing computation in game theory. With Gambit, you can build, analyze, and explore game models.

Use Gambit's graphical interface to get intuition about simple games, or the command-line tools and Python scripting API to support your world-class research and practical applications.

http://www.gambit-project.org/

Gambit is a set of software tools for doing computation on finite, noncooperative games. These comprise a graphical interface for interactively building and analyzing general games in extensive or strategy form; a number of command-line tools for computing Nash equilibria and other solution concepts in games; and, a set of file formats for storing and communicating games to external tools.
http://gambit.sourceforge.net/gambit14/intro.html

http://gambit.sourceforge.net/gambit14/ideas.html

http://www.git-scm.com/book/en/v2
http://gambit.git.sourceforge.net/git/gitweb-index.cgi
http://gambit.git.sourceforge.net/git/gitweb.cgi?p=gambit/gambit;a=tree


Modelling behaviour
Game theory in practice
Computing: Software that models human behaviour can make forecasts, outfox rivals and transform negotiations

http://www.economist.com/node/21527025

FOR a man who claims to lack expertise in the field, Bruce Bueno de Mesquita, an academic at New York University, has made some impressively accurate political forecasts. In May 2010 he predicted that Egypt's president, Hosni Mubarak, would fall from power within a year. Nine months later Mr Mubarak fled Cairo amid massive street protests. In February 2008 Mr Bueno de Mesquita predicted that Pakistan's president, Pervez Musharraf, would leave office by the end of summer. He was gone before September. Five years before the death of Iran's Ayatollah Khomeini in 1989, Mr Bueno de Mesquita correctly named his successor, and, since then, has made hundreds of prescient forecasts as a consultant both to foreign governments and to America's State Department, Pentagon and intelligence agencies. What is the secret of his success? “I don't have insights—the game does,” he says.

LIST OF GAME THEORY SOFTWARE
Game theoretic software

Population Dynamics Toolbox

This toolbox for evolutionary game theory is implemented in Matlab and is designed to facilitate the implementation of any game with different evolutionary dynamics. Here is a PDF file with detailed documentation,

Game Theory Explorer

GTE is web-based software for the interactive creation and equilibrium analysis of games in extensive and strategic form.

Gambit

Gambit is a library of game theory software and tools for the construction and analysis of finite extensive and strategic games.

GamePlan

by Jean-Pierre Langlois from San Francisco State University is a Windows application for creating and analyzing games.

Solve a Bimatrix Game

This algorithm by Rahul Savani enumerates all equilibria of a bimatrix game.

lrs home page

lrslib is a self-contained ANSI C implementation as a callable library of the reverse search algorithm for vertex enumeration/convex hull problems by David Avis.

TUGlab

Transferable utility game theory Matlab toolboxes maintained by the Santiago Game Theory Group.

Political Game Theory

http://www.amazon.com/s/ref=nb_sb_noss_1?url=search-alias%3Dstripbooks&field-keywords=political+game+theory

International Relations Theory: The Game-Theoretic Approach

Paperback – March 16, 2015
by Professor Andrew H. Kydd (Author)
http://www.amazon.com/International-Relations-Theory-Game-Theoretic-Approach/dp/110769423X/
The book focuses on noncooperative game theory and its application to international relations, political economy, and American and comparative politics. Special attention is given to models of four topics: bargaining, legislative voting rules, voting in mass elections, and deterrence.
Game Theory for Political Scientists: James D. Morrow ...
www.amazon.com/Theory-Political.../dp/0691034303
Amazon.com, Inc.

Game Theory for Political Scientists
James D. Morrow
http://press.princeton.edu/titles/5590.html

Game theory is the mathematical analysis of strategic interaction. In the fifty years since the appearance of von Neumann and Morgenstern's classic Theory of Games and Economic Behavior (Princeton, 1944), game theory has been widely applied to problems in economics. Until recently, however, its usefulness in political science has been underappreciated, in part because of the technical difficulty of the methods developed by economists. James Morrow's book is the first to provide a standard text adapting contemporary game theory to political analysis. It uses a minimum of mathematics to teach the essentials of game theory and contains problems and their solutions suitable for advanced undergraduate and graduate students in all branches of political science.

Morrow begins with classical utility and game theory and ends with current research on repeated games and games of incomplete information. The book focuses on noncooperative game theory and its application to international relations, political economy, and American and comparative politics. Special attention is given to models of four topics: bargaining, legislative voting rules, voting in mass elections, and deterrence. An appendix reviews relevant mathematical techniques. Brief bibliographic essays at the end of each chapter suggest further readings, graded according to difficulty. This rigorous but accessible introduction to game theory will be of use not only to political scientists but also to psychologists, sociologists, and others in the social sciences.

Game Theory and Political Theory
MIT Open Course
http://ocw.mit.edu/courses/political-science/17-881-game-theory-and-political-theory-fall-2004/

How Game Theory Explains Washington's Horrible Gridlock
http://www.theatlantic.com/politics/archive/2013/01/how-game-theory-explains-washingtons-horrible-gridlock/267142/

Political Game Theory
An Introduction
AUTHORS:
Nolan McCarty, Princeton University, New Jersey
Adam Meirowitz, Princeton University, New Jersey
DATE PUBLISHED: January 2007
AVAILABILITY: Available
FORMAT: Hardback
ISBN: 9780521841078

http://www.cambridge.org/us/academic/subjects/politics-international-relations/politics-general-interest/political-game-theory-introduction?format=HB

ECONOMIST
Technology Quarterly: Q3 2011
Modelling behaviour
Game theory in practice
Computing: Software that models human behaviour can make forecasts, outfox rivals and transform negotiations
http://www.economist.com/node/21527025


How much of Game Theory is really used in every day international politics, wars, and conflicts?
https://www.quora.com/How-much-of-Game-Theory-is-really-used-in-every-day-international-politics-wars-and-conflicts


BitQuant Research Laboratories

Open source GIT SW
We are a mom-and-pop research lab and HK startup.
http://www.bitquant.com.hk/
wiki
https://en.wikipedia.org/wiki/Game_theory

Politics: EXISTING APPROACHES, APPLICATIONS AND TOOLS

Discovering the relationship of the G20 members using Data Mining

Posted by Leandro Guerra on February 16, 2015 at 10:29am
http://www.datasciencecentral.com/profiles/blogs/discovering-the-relationship-of-the-g20-members-using-data-mining

https://www.google.com/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=Machine+learning+political+campaign

1. PolyticIt
https://gigaom.com/2012/06/25/can-a-big-data-product-level-the-playing-field-in-politics/

2. Policy by the Numbers
http://policybythenumbers.blogspot.com/2015/04/how-do-political-campaigns-use-data.html

3. Obama campaign’s chief data guy gets candid about the data strategy that won the election
http://venturebeat.com/2013/05/19/obama-campaigns-chief-data-guy-gets-candid-about-the-data-strategy-that-won-the-election/
After helping to get the president re-elected, Ghani now works as chief data scientist at University of Chicago. He’ll be running a three-month summer program on “Data Science for Social Good” at the university for which he’s currently accepting applications from students across the country. Ghani is also working on a social good analytics startup called EdgeFlip.

http://chicagoinno.streetwise.co/2015/03/25/edgeflip-raises-50k-from-new-ventures-media-innovation-fund/

Public Policy 30510: Data Analytics for Campaigns

http://www.rayidghani.com/wordpress/teaching/public-policy-30510-data-analytics-for-campaigns/

4. How can machine learning and predictive analysis help in modeling the campaign strategy for Narendra Modi's victory in 2014 polls in India?

https://www.quora.com/How-can-machine-learning-and-predictive-analysis-help-in-modeling-the-campaign-strategy-for-narendra-modis-victory-in-2014-polls-in-india

5. ProPublica's Message Machine and its conclusions about email targeting in the 2012 election campaigns.
https://civic.mit.edu/blog/jskao/email-targeting-in-2012-political-campaigns
Using NLP and machine learning, ProPublica modeled the data and ...

Top Political Campaign Software Products

http://www.capterra.com/political-campaign-software/

1. Trail BlazerWin Your Election - trailblz.com‎
Trail Blazer - Powerful software for political campaigns and PACs.

2. CallFire
https://www.callfire.com

3. Hoop.la
http://www.hoop.la

Presidential IQ, Openness, Intellectual Brilliance, and Leadership: Estimates and Correlations for 42 U.S. Chief Executives
 Author(s): Dean Keith Simonton
 Source: Political Psychology, Vol. 27, No. 4 (Aug., 2006), pp. 511-526
Published by: International Society of Political Psychology Stable URL: http://www.jstor.org/stable/3792393 Accessed: 04/03/2010 02:53
http://www.acsu.buffalo.edu/~jcampbel/documents/SimontonPresIQ2006.pdf

Poindexter in Chief: Presidential IQs and Success in the Oval Office
http://www.usnews.com/news/blogs/data-mine/2015/05/27/poindexter-in-chief-presidential-iqs-and-success-in-the-oval-office

Presentation Effectiveness: A Free Guide to Effective Public Speaking

http://www.dalecarnegie.com/ebook/presentation-effectiveness-speak-more-effectively-guide/

Communicate Effectively
Get Rid of Nerves
Speak with Confidence
Win Your Audience

API MANAGERS

Open Source REST API Platform

WSO2
http://wso2.com/landing/ppc/api-manager/?gclid=CO6pvJzblsgCFQpDaQodeFQJDw

Amazon Efforts and Offerings
Cloudy Machine Learning For The Masses
http://www.theplatform.net/2015/04/10/cloudy-machine-learning-for-the-masses/

Amazon Machine Learning (AML) is based on the company’s own experiences with predictive analytics

http://aws.amazon.com/machine-learning/faqs/

Receive twelve months of access to the AWS Free Tier and enjoy AWS Basic Support features including, 24x7x365 customer service, support forums, and more.

Please note that Amazon Machine Learning is not currently available on the AWS Free Tier.

Open Source API Gateway - github.com

‎Microservice & API Management Layer KONG

Apache Licensehttps://github.com/mashape/kong

Dream Factory

Powerful REST APIs made Simple

https://www.dreamfactory.com/features

Swagger

http://swagger.io/

Deployd

http://deployd.com/

Analytics For API Platform
Akana
http://akana.com/solution/api-management
MuleSoft
https://www.mulesoft.com/platform/api/api-analytics
Apigee
http://apigee.com/about/products/api-management

Microservices

microservices rest api for machine learning

Microservice Runtime Predictive Services
http://docs.seldon.io/pluggable-prediction-algorithms.html

Microservice runtime prediction services allow you to add any custom predictive scorer into Seldon rather than being limited to the ones available in the core Java server. The following sections describe the various components:
Offline model creation
Online external prediction
Microservices REST API
Zookeeper configuration
Prepackaged Microservices
Vowpal Wabbit predictive scorer
XGBoost predictive scorer
Creating your own Predictive Scorer
Example python predictive scoring template
Example python predictive scoring with Vowpal Wabbit
Offline Model

You can utilize any method to create the offline model. You can use the seldon ‘’‘/events’’’ endpoints in the REST andjavascript APIs to inject the events. Some examples of creating models with Vowlpal Wabbit and XGBoost are provided.
Online Predictive Scoring

For the online predictive scoring of an external algoithm we provide a REST API definition that any external predictive scoring algorithm must conform to. You would create a component that satisfies this REST API and publish its endpoint within the Seldon zookeeper configuration for the client you want to have use it. These steps are explained below. Finally, we have provided a python reference template that satisfies this REST API that you can use to write your own external recommender along with an example interface to use Vowpal Wabbit as the online predictive scorer.
Microservices REST API

Developing applications with a microservice architecture (SVforum, microservices meetup)
http://www.slideshare.net/chris.e.richardson/developing-apps-with-a-microservice-architecture-svforum-microservices-meetup

CQRS stands for Command Query Responsibility Segregation. It's a pattern that I first heard described by Greg Young. At its heart is the notion that you can use a different model to update information than the model you use to read information. Jul 14, 2011

CQRS - Martin Fowler
martinfowler.com/bliki/CQRS.html
Martin Fowler

Google Meetup - 

www.meetup.com/sv-jug/events/226018379/
Developing event-driven microservices with event sourcing and CQRS

Modern, cloud-native applications typically use a microservices architecture in conjunction with NoSQL and/or sharded relational databases. However, in order to successfully use this approach you need to solve some distributed data management problems including how to maintain consistency between multiple databases without using 2PC. In this talk you will learn more about these issues and how to solve them by using an event-driven architecture. We will describe how event sourcing and Command Query Responsibility Segregation (CQRS) are a great way to realize an event-driven architecture. You will learn about a simple yet powerful approach for building, modern, scalable applications.

Chris Richardson is a developer and architect. He is a Java Champion, a JavaOne rock star and the author of POJOs in Action, which describes how to build enterprise Java applications with frameworks such as Spring and Hibernate. Chris was also the founder of the original CloudFoundry.com, an early Java PaaS for Amazon EC2. He is the creator of microservices.io and is working on his third startup: a platform for developing reactive microservices. Chris also does microservices-related consulting and training. Blog: http://plainoldobjects.com/, Twitter: @crichardson

API Testing
http://katrinatester.blogspot.com/2015/09/api-web-services-microservices-testing.html

ML for Management Consulting

MANAGEMENT CONSULTING WITH ML AND GAME THEORY

The Future of Management Consulting and Analytics
http://www.quantifye.co/blog/the-future-of-management-consulting-and-analytics

Making game theory work for managers
A new model, rejecting solutions optimal only for a single precisely defined future, generates answers representing the best compromise between risks and opportunities in all likely futures.
http://www.mckinsey.com/insights/strategy/making_game_theory_work_for_managers

Advances in Electrical Engineering and Computational Science

https://books.google.com/books?id=NEqlTmiEFAYC

https://books.google.com/books?id=tPkjk5s-GHgC&pg=PA171

https://www.cs.umd.edu/~basili/publications/proceedings/P120.pdf
A STATISTICAL NEURAL NETWORK FRAMEWORK FOR RISK MANAGEMENT PROCESS From the Proposal to its Preliminary Validation for Efficiency Salvatore Alessandro Sarcià, Giovanni Cantone Dip. di Informatica, Sistemi e Produzione, Università di Roma Tor Vergata, via del Politecnico 1, 00133 Roma, Italy sarcia@, cantone@uniroma2.it Victor R. Basili Dept. of Computer Science, University of Maryland, A.V. Williams Bldg. 115, College Park 20742, MD, USA basili@cs.umd.edu Keywords: Risk Management Process, Artificial Neural Networks, Experimental Software Engineering, Prior Probability, Posterior Probability, Bayes’ Theorem, Computational Software Engineering. Abstract: This paper enhances the currently available formal risk management models and related frameworks by providing an independent mechanism for checking out their results. It provides a way to compare the historical data on the risks identified by similar projects to the risk found by each framework Based on direct queries to stakeholders, existing approaches provide a mechanism for estimating the probability of achieving software project objectives before the project starts (Prior probability). However, they do not estimate the probability that objectives have actually been achieved, when risk events have occurred during project development. This involves calculating the posterior probability that a project missed its objectives, or, on the contrary, the probability that the project has succeeded. This paper provides existing frameworks with a way to calculate both prior and posterior probability. The overall risk evaluation, calculated by those two probabilities, could be compared to the evaluations that each framework has found within its own process. Therefore, the comparison is performed between what those frameworks assumed and what the historical data suggested both before and during the project. This is a control mechanism because, if those comparisons do not agree, further investigations could be carried out. A case study is presented that provides an efficient way to deal with those issues by using Artificial Neural Networks (ANN) as a statistical tool (e.g., regression and probability estimator). That is, we show that ANN can automatically derive from historical data both prior and posterior probability estimates. This paper shows the verification by simulation of the proposed approach. 

https://books.google.com/books?id=Wg7LBQAAQBAJ

Title	Risk Assessment and Decision Analysis with Bayesian Networks
Authors	Norman Fenton, Martin Neil
Edition	illustrated
Publisher	CRC Press, 2013
ISBN	1439809119, 9781439809112
Length	524 pages

Trader Says...

How To Beat Every Hedge Fund in Just 2 Trades & 4 Hours A Day

Submitted by Tyler Durden on 09/09/2015 15:50 -0400

http://www.zerohedge.com/news/2015-09-09/how-beat-every-hedge-fund-just-2-trades-4-hours-day

Step 1: Put on Pants;

Step 2: Buy S&P 500 Futures at Midnight ET;

Step 3: Sell S&P 500 Futures at 4amET;

Step 4: Go back to bed...