Data assurance in opaque computations

The chess endgame is increasingly being seen through the lens of, and therefore effectively defined by, a data ‘model’ of itself. It is vital that such models are clearly faithful to the reality they purport to represent. This paper examines that issue and systems engineering responses to it, using the chess endgame as the exemplar scenario. A structured survey has been carried out of the intrinsic challenges and complexity of creating endgame data by reviewing the past pattern of errors during work in progress, surfacing in publications and occurring after the data was generated. Specific measures are proposed to counter observed classes of error-risk, including a preliminary survey of techniques for using state-of-the-art verification tools to generate EGTs that are correct by construction. The approach may be applied generically beyond the game domain

FinalGen revisited: new discoveries

Romero’s FINALGEN of 2012 creates designer endgame tables for specific chess positions that feature no more than one non-pawn piece per side. Larger hard discs and faster solid-state discs have extended the reach of this software and encouraged its greater use. Some new discoveries illustrate here what is now feasible and how FINALGEN may be combined with other tools to reach definitive and likely truths

Use-driven concept formation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 161-165).When faced with a complex task, humans often identify domain-specific concepts that make the task more tractable. In this thesis, I investigate the formation of domain-specific concepts of this sort. I propose a set of principles for formulating domain-specific concepts, including a new inductive bias that I call the equivalence class principle. I then use the domain of two-player, perfect-information games to test and refine those principles. I show how the principles can be applied in a semiautomated fashion to identify strategically-important visual concepts, discover highlevel structure in a game's state space, create human-interpretable descriptions of tactics, and uncover both offensive and defensive strategies within five deterministic, perfect-information games that have up to forty-two million states apiece. I introduce a visualization technique for networks that discovers a new strategy for exploiting an opponent's mistakes in lose tic-tac-toe; discovers the optimal defensive strategies in five and six men's morris; discovers the optimal offensive strategies in pong hau k'i, tic-tac-toe, and lose tic-tac-toe; simplifies state spaces by up to two orders of magnitude; and creates a hierarchical depiction of a game's state space that allows the user to explore the space at multiple levels of granularity. I also introduce the equivalence class principle, an inductive bias that identifies concepts by building connections between two representations in the same domain. I demonstrate how this principle can be used to rediscover visual concepts that would help a person learn to play a game, propose a procedure for using such concepts to create succinct, human-interpretable descriptions of offensive and defensive tactics, and show that these tactics can compress important information in the five men's morris state space by two orders of magnitude.by Jennifer M. Roberts.Ph.D

Welfare Diplomacy: Benchmarking Language Model Cooperation

The growing capabilities and increasingly widespread deployment of AI systems necessitate robust benchmarks for measuring their cooperative capabilities. Unfortunately, most multi-agent benchmarks are either zero-sum or purely cooperative, providing limited opportunities for such measurements. We introduce a general-sum variant of the zero-sum board game Diplomacy -- called Welfare Diplomacy -- in which players must balance investing in military conquest and domestic welfare. We argue that Welfare Diplomacy facilitates both a clearer assessment of and stronger training incentives for cooperative capabilities. Our contributions are: (1) proposing the Welfare Diplomacy rules and implementing them via an open-source Diplomacy engine; (2) constructing baseline agents using zero-shot prompted language models; and (3) conducting experiments where we find that baselines using state-of-the-art models attain high social welfare but are exploitable. Our work aims to promote societal safety by aiding researchers in developing and assessing multi-agent AI systems. Code to evaluate Welfare Diplomacy and reproduce our experiments is available at https://github.com/mukobi/welfare-diplomacy

Synthetic steganography: Methods for generating and detecting covert channels in generated media

Issues of privacy in communication are becoming increasingly important. For many people and businesses, the use of strong cryptographic protocols is sufficient to protect their communications. However, the overt use of strong cryptography may be prohibited or individual entities may be prohibited from communicating directly. In these cases, a secure alternative to the overt use of strong cryptography is required. One promising alternative is to hide the use of cryptography by transforming ciphertext into innocuous-seeming messages to be transmitted in the clear. ^ In this dissertation, we consider the problem of synthetic steganography: generating and detecting covert channels in generated media. We start by demonstrating how to generate synthetic time series data that not only mimic an authentic source of the data, but also hide data at any of several different locations in the reversible generation process. We then design a steganographic context-sensitive tiling system capable of hiding secret data in a variety of procedurally-generated multimedia objects. Next, we show how to securely hide data in the structure of a Huffman tree without affecting the length of the codes. Next, we present a method for hiding data in Sudoku puzzles, both in the solved board and the clue configuration. Finally, we present a general framework for exploiting steganographic capacity in structured interactions like online multiplayer games, network protocols, auctions, and negotiations. Recognizing that structured interactions represent a vast field of novel media for steganography, we also design and implement an open-source extensible software testbed for analyzing steganographic interactions and use it to measure the steganographic capacity of several classic games. ^ We analyze the steganographic capacity and security of each method that we present and show that existing steganalysis techniques cannot accurately detect the usage of the covert channels. We develop targeted steganalysis techniques which improve detection accuracy and then use the insights gained from those methods to improve the security of the steganographic systems. We find that secure synthetic steganography, and accurate steganalysis thereof, depends on having access to an accurate model of the cover media

Approximation and Relaxation Approaches for Parallel and Distributed Machine Learning

Large scale machine learning requires tradeoffs. Commonly this tradeoff has led practitioners to choose simpler, less powerful models, e.g. linear models, in order to process more training examples in a limited time. In this work, we introduce parallelism to the training of non-linear models by leveraging a different tradeoff--approximation. We demonstrate various techniques by which non-linear models can be made amenable to larger data sets and significantly more training parallelism by strategically introducing approximation in certain optimization steps. For gradient boosted regression tree ensembles, we replace precise selection of tree splits with a coarse-grained, approximate split selection, yielding both faster sequential training and a significant increase in parallelism, in the distributed setting in particular. For metric learning with nearest neighbor classification, rather than explicitly train a neighborhood structure we leverage the implicit neighborhood structure induced by task-specific random forest classifiers, yielding a highly parallel method for metric learning. For support vector machines, we follow existing work to learn a reduced basis set with extremely high parallelism, particularly on GPUs, via existing linear algebra libraries. We believe these optimization tradeoffs are widely applicable wherever machine learning is put in practice in large scale settings. By carefully introducing approximation, we also introduce significantly higher parallelism and consequently can process more training examples for more iterations than competing exact methods. While seemingly learning the model with less precision, this tradeoff often yields noticeably higher accuracy under a restricted training time budget

Java, Java, Java: Object-Oriented Problem Solving

Open Access Textbook from Open Textbook Library: Java, Java, Java, 3e was previously published by Pearson Education, Inc. The first edition (2000) and the second edition (2003) were published by Prentice-Hall. In 2010 Pearson Education, Inc. reassigned the copyright to the authors, and we are happy now to be able to make the book available under an open source license. This PDF edition of the book is available under a Creative Commons Attribution 4.0 International License, which allows the book to be used, modified, and shared with attribution: (https://creativecommons.org/licenses/by/4.0/). – Ralph Morelli and Ralph Walde – Hartford, CT – December 30, 201

Achieving broad access to satellite control research with zero robotics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.This thesis was scanned as part of an electronic thesis pilot project.Cataloged from PDF version of thesis.Includes bibliographical references (p. 307-313).Since operations began in 2006, the SPHERES facility, including three satellites aboard the International Space Station (ISS), has demonstrated many future satellite technologies in a true microgravity environment and established a model for developing successful ISS payloads. In 2009, the Zero Robotics program began with the goal of leveraging the resources of SPHERES as a tool for Science, Technology, Engineering, and Math education through a unique student robotics competition. Since the first iteration with two teams, the program has grown over four years into an international tournament involving more than two thousand student competitors and has given hundreds of students the experience of running experiments on the ISS. Zero Robotics tournaments involve an annually updated challenge motivated by a space theme and designed to match the hardware constraints of the SPHERES facility. The tournament proceeds in several phases of increasing difficulty, including a multi-week collaboration period where geographically separated teams work together through the provided tools to write software for SPHERES. Students initially compete in a virtual, online simulation environment, then transition to hardware for the final live championship round aboard the ISS. Along the way, the online platform ensures compatibility with the satellite hardware and provides feedback in the form of 3D simulation animations. During each competition phase, a continuous scoring system allows competitors to incrementally explore new strategies while striving for a seat in the championship. This thesis will present the design of the Zero Robotics competition and supporting online environment and tools that enable users from around the world to successfully write computer programs for satellites. The central contribution is a framework for building virtual platforms that serve as surrogates for limited availability hardware facilities. The framework includes the elaboration of the core principles behind the design of Zero Robotics along with examples and lessons from the implementation of the competition. The virtual platform concept is further extended with a web-based architecture for writing, compiling, simulating, and analyzing programs for a dynamic robot. A standalone and key enabling component of the architecture is a pattern for building fast, high fidelity, web-based simulations. For control of the robots, an easy to use programming interface for controlling 6 degree-of-freedom (6DOF) satellites is presented, along with a lightweight supervisory control law to prevent collisions between satellites without user action. This work also contributes a new form of student robotics competition, including the unique features of model-based online simulation, programming, 6DOF dynamics, a multi-week team collaboration phase, and the chance to test satellites aboard the ISS. Scoring during the competition is made possible by possible by a game-agnostic scoring algorithm, which has been demonstrated during a tournament season and improved for responsiveness. Lastly, future directions are suggested for improving the tournament including a detailed initial exploration of creating open-ended Monte Carlo analysis tools.by Jacob G. Katz.Ph.D