David H. Wolpert

Jens Kipper

Entropy, February, 2024

The computational power of a human society: a new model of social evolution.

[BibT_eX]

[DOI]

Kyle Harper

CoRR, 2024

Implications of computer science theory for the simulation hypothesis.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Stochastic Thermodynamics of Multiple Co-Evolving Systems - Beyond Multipartite Processes.

[BibT_eX]

[DOI]

Farita Tasnim

Entropy, July, 2023

Is stochastic thermodynamics the key to understanding the energy costs of computation?

[BibT_eX]

[DOI]

Vijay Balasubramanian

CoRR, 2023

Game Manipulators - the Strategic Implications of Binding Contracts.

[BibT_eX]

[DOI]

Maria Alejandra Ramirez

CoRR, 2023

The fundamental thermodynamic costs of communication.

[BibT_eX]

[DOI]

Farita Tasnim

Nahuel Freitas

CoRR, 2023

2022

Social Scale and Collective Computation: Does Information Processing Limit Rate of Growth in Scale?

[BibT_eX]

[DOI]

Timothy A. Kohler

Darcy Bird

J. Soc. Comput., 2022

What can we know about that which we cannot even imagine?

[BibT_eX]

[DOI]

CoRR, 2022

2021

The Past as a Stochastic Process.

[BibT_eX]

[DOI]

Manfred D. Laubichler

CoRR, 2021

The Implications of the No-Free-Lunch Theorems for Meta-induction.

[BibT_eX]

[DOI]

CoRR, 2021

The state dependence of integrated, instantaneous, and fluctuating entropy production in quantum and classical processes.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Noisy Deductive Reasoning: How Humans Construct Math, and How Math Constructs Universes.

[BibT_eX]

[DOI]

David Kinney

CoRR, 2020

Entropy production and thermodynamics of information under protocol constraints.

[BibT_eX]

[DOI]

CoRR, 2020

What is important about the No Free Lunch theorems?

[BibT_eX]

[DOI]

CoRR, 2020

Minimum entropy production in multipartite processes due to neighborhood constraints.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes.

[BibT_eX]

[DOI]

Mykel J. Kochenderfer

IEEE Trans. Intell. Transp. Syst., 2019

How Much Would You Pay to Change a Game before Playing It?

[BibT_eX]

[DOI]

Justin Grana

Entropy, 2019

Nonlinear Information Bottleneck.

[BibT_eX]

[DOI]

Brendan D. Tracey

Entropy, 2019

Thermodynamic costs of Turing Machines.

[BibT_eX]

[DOI]

CoRR, 2019

Uncertainty relations and fluctuation theorems for Bayes nets.

[BibT_eX]

[DOI]

CoRR, 2019

Thermodynamic Computing.

[BibT_eX]

[DOI]

CoRR, 2019

Stochastic thermodynamics of computation.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Beyond Number of Bit Erasures: New Complexity Questions Raised by Recently Discovered Thermodynamic Costs of Computation.

[BibT_eX]

[DOI]

Joshua A. Grochow

SIGACT News, 2018

Exact, complete expressions for the thermodynamic costs of circuits.

[BibT_eX]

[DOI]

David Hilton Wolpert

CoRR, 2018

2017

Bias-Variance Trade-Offs: Novel Applications.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Coarse-Graining and the Blackwell Order.

[BibT_eX]

[DOI]

Entropy, 2017

Constraints on physical reality arising from a formalization of knowledge.

[BibT_eX]

[DOI]

CoRR, 2017

Number of hidden states needed to physically implement a given conditional distribution.

[BibT_eX]

[DOI]

Jeremy A. Owen

CoRR, 2017

The minimal hidden computer needed to implement a visible computation.

[BibT_eX]

[DOI]

Jeremy A. Owen

CoRR, 2017

Modeling Social Organizations as Communication Networks.

[BibT_eX]

[DOI]

CoRR, 2017

2016

A likelihood ratio anomaly detector for identifying within-perimeter computer network attacks.

[BibT_eX]

[DOI]

J. Netw. Comput. Appl., 2016

Correction: Wolpert, D.H. The Free Energy Requirements of Biological Organisms; Implications for Evolution. Entropy 2016, 18, 138.

[BibT_eX]

[DOI]

Entropy, 2016

The Free Energy Requirements of Biological Organisms; Implications for Evolution.

[BibT_eX]

[DOI]

Entropy, 2016

Thermodynamic cost due to changing the initial distribution over states.

[BibT_eX]

[DOI]

CoRR, 2016

A Likelihood Ratio Detector for Identifying Within-Perimeter Computer Network Attacks.

[BibT_eX]

[DOI]

CoRR, 2016

Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach.

[BibT_eX]

[DOI]

Rémi Lam

Karen Willcox

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2014

A framework for optimal high-level descriptions in science and engineering - preliminary report.

[BibT_eX]

[DOI]

CoRR, 2014

Information geometry of influence diagrams and noncooperative games.

[BibT_eX]

[DOI]

CoRR, 2014

2013

Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate the Future.

[BibT_eX]

[DOI]

Proceedings of the Decision Making and Imperfection, 2013

Ubiquity symposium: Evolutionary computation and the processes of life: what the no free lunch theorems really mean: how to improve search algorithms.

[BibT_eX]

[DOI]

Ubiquity, 2013

Cyber-Physical Security: A Game Theory Model of Humans Interacting Over Control Systems.

[BibT_eX]

[DOI]

IEEE Trans. Smart Grid, 2013

The lesson of Newcomb's paradox.

[BibT_eX]

[DOI]

Gregory Benford

Synth., 2013

Predicting Behavior in Unstructured Bargaining with a Probability Distribution.

[BibT_eX]

[DOI]

James W. Bono

J. Artif. Intell. Res., 2013

Estimating Functions of Distributions Defined over Spaces of Unknown Size.

[BibT_eX]

[DOI]

Simon DeDeo

Entropy, 2013

Using Machine Learning to Improve Stochastic Optimization.

[BibT_eX]

[DOI]

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

2012

Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate The Future

[BibT_eX]

[DOI]

CoRR, 2012

Predicting the behavior of interacting humans by fusing data from multiple sources.

[BibT_eX]

[DOI]

Erik J. Schlicht

Ritchie Lee

Mykel J. Kochenderfer

Brendan D. Tracey

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Towards a bayesian network game framework for evaluating DDoS attacks and defense.

[BibT_eX]

[DOI]

Proceedings of the ACM Conference on Computer and Communications Security, 2012

2011

Using Supervised Learning to Improve Monte Carlo Integral Estimation

[BibT_eX]

[DOI]

Brendan D. Tracey

Juan J. Alonso

CoRR, 2011

Game theoretic modeling of pilot behavior during mid-air encounters

[BibT_eX]

[DOI]

Ritchie Lee

CoRR, 2011

2010

Bias-Variance Trade-offs: Novel Applications.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning, 2010

Why income comparison is rational.

[BibT_eX]

[DOI]

Games Econ. Behav., 2010

Hysteresis effects of changing parameters of noncooperative games

[BibT_eX]

[DOI]

CoRR, 2010

PGT: A Statistical Approach to Prediction and Mechanism Design.

[BibT_eX]

[DOI]

James W. Bono

Proceedings of the Advances in Social Computing, 2010

Inference Concerning Physical Systems.

[BibT_eX]

[DOI]

Proceedings of the Programs, Proofs, Processes, 6th Conference on Computability in Europe, 2010

2009

Trembling hand perfection for mixed quantal/best response equilibria.

[BibT_eX]

[DOI]

Int. J. Game Theory, 2009

What does Newcomb's paradox teach us?

[BibT_eX]

[DOI]

Gregory Benford

CoRR, 2009

2008

Distributed Constrained Optimization with Semicoordinate Transformations

[BibT_eX]

[DOI]

CoRR, 2008

Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation for the CE Method

[BibT_eX]

[DOI]

CoRR, 2008

Managing Multiple Interacting Adaptive Systems Via Game Theory.

[BibT_eX]

[DOI]

Nilesh V. Kulkarni

Proceedings of the NASA/ESA Conference on Adaptive Hardware and Systems, 2008

2007

Physical limits of inference

[BibT_eX]

[DOI]

CoRR, 2007

Parametric Learning and Monte Carlo Optimization

[BibT_eX]

[DOI]

CoRR, 2007

Using self-dissimilarity to quantify complexity.

[BibT_eX]

[DOI]

Complex., 2007

2006

Advances in Distributed Optimization Using Probability Collectives.

[BibT_eX]

[DOI]

Charlie E. M. Strauss

Adv. Complex Syst., 2006

2005

Coevolutionary free lunches.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2005

A Predictive Theory of Games

[BibT_eX]

[DOI]

CoRR, 2005

A comparative study of probability collectives based multi-agent systems and genetic algorithms.

[BibT_eX]

[DOI]

Chien-Feng Huang

Charlie E. M. Strauss

Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004

Metrics for more than two points at once

[BibT_eX]

[DOI]

CoRR, 2004

Information Theory - The Bridge Connecting Bounded Rational Game Theory and Statistical Physics

[BibT_eX]

[DOI]

CoRR, 2004

Distributed Adaptive Control: Beyond Single-Instant, Discrete Control Variables.

[BibT_eX]

[DOI]

Proceedings of the Monitoring, Security, and Rescue Techniques in Multiagent Systems, 2004

Distributed control by Lagrangian steepest descent.

[BibT_eX]

[DOI]

Proceedings of the 43rd IEEE Conference on Decision and Control, 2004

Product Distribution Theory for Control of Multi-Agent Systems.

[BibT_eX]

[DOI]

Chiu Fan Lee

Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), 2004

Adaptive, Distributed Control of Constrained Multi-Agent Systems.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), 2004

2003

Improving Search Algorithms by Using Intelligent Coordinates

[BibT_eX]

[DOI]

Esfandiar Bandari

CoRR, 2003

Product Distribution Field Theory

[BibT_eX]

[DOI]

CoRR, 2003

Collectives for the Optimal Combination of Imperfect Objects

[BibT_eX]

[DOI]

CoRR, 2003

Providing Effective Access to Shared Resources: A COIN Approach.

[BibT_eX]

[DOI]

Proceedings of the Engineering Self-Organising Systems, 2003

2002

Collective Intelligence, Data Routing and Braess' Paradox.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2002

Designing agent collectives for systems with Markovian dynamics.

[BibT_eX]

[DOI]

John W. Lawson

Proceedings of the First International Joint Conference on Autonomous Agents & Multiagent Systems, 2002

Learning sequences of actions in collectives of autonomous agents.

[BibT_eX]

[DOI]

Adrian K. Agogino

Proceedings of the First International Joint Conference on Autonomous Agents & Multiagent Systems, 2002

The Design of Collectives of Agents to Control Non-Markovian Systems.

[BibT_eX]

[DOI]

John W. Lawson

Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001

Remarks on a recent paper on the "no free lunch" theorems.

[BibT_eX]

[DOI]

Mario Köppen

IEEE Trans. Evol. Comput., 2001

Optimal Payoff Functions for Members of Collectives.

[BibT_eX]

[DOI]

Adv. Complex Syst., 2001

Reinforcement Learning in Distributed Domains: Beyond Team Games.

[BibT_eX]

Joseph Sill

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

2000

On the computational capabilities of physical systems part II: relationship with conventional computer science

[BibT_eX]

[DOI]

CoRR, 2000

On the computational capabilities of physical systems part I: the impossibility of infallible computation

[BibT_eX]

[DOI]

CoRR, 2000

Adaptivity in agent-based routing for data networks.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on Autonomous Agents, 2000

Collective Intelligence and Braess' Paradox.

[BibT_eX]

[DOI]

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999

An Efficient Method To Estimate Bagging's Generalization Error.

[BibT_eX]

[DOI]

Mach. Learn., 1999

Linearly Combining Density Estimators via Stacking.

[BibT_eX]

[DOI]

Padhraic Smyth

Mach. Learn., 1999

Guest Editors' Introduction.

[BibT_eX]

[DOI]

Philip K. Chan

Salvatore J. Stolfo

Mach. Learn., 1999

An Introduction to Collective Intelligence

[BibT_eX]

[DOI]

CoRR, 1999

Collective Intelligence for Control of Distributed Dynamical Systems

[BibT_eX]

[DOI]

Kevin R. Wheeler

CoRR, 1999

Avoiding Braess' Paradox through Collective Intelligence

[BibT_eX]

[DOI]

CoRR, 1999

General Principles of Learning-Based Multi-Agent Systems.

[BibT_eX]

[DOI]

Kevin R. Wheeler

Proceedings of the Third Annual Conference on Autonomous Agents, 1999

1998

Bandit problems and the exploration/exploitation tradeoff.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 1998

Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers.

[BibT_eX]

[DOI]

Emanuel Knill

Tal Grossman

Stat. Comput., 1998

Using Collective Intelligence to Route Internet Traffic.

[BibT_eX]

[DOI]

Jeremy Frank

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997

No free lunch theorems for optimization.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 1997

On Bias Plus Variance.

[BibT_eX]

[DOI]

Neural Comput., 1997

Stacked Density Estimation.

[BibT_eX]

[DOI]

Padhraic Smyth

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Anytime Exploratory Data Analysis for Massive Data Sets.

[BibT_eX]

[DOI]

Padhraic Smyth

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

1996

The Existence of A Priori Distinctions Between Learning Algorithms.

[BibT_eX]

[DOI]

Neural Comput., 1996

The Lack of A Priori Distinctions Between Learning Algorithms.

[BibT_eX]

[DOI]

Neural Comput., 1996

What makes an optimization problem hard?

[BibT_eX]

[DOI]

Complex., 1996

Bias Plus Variance Decomposition for Zero-One Loss Functions.

[BibT_eX]

Ron Kohavi

Proceedings of the Machine Learning, 1996

1993

Bayesian Backpropagation Over I-O Functions Rather Than Weights.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

Stacked generalization.

[BibT_eX]

[DOI]

Neural Networks, 1992

On the Connection between In-sample Testing and Generalization Error.

[BibT_eX]

[DOI]

Complex Syst., 1992

On the Use of Evidence in Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1990

Constructing a generalizer superior to NETtalk via a mathematical theory of generalization.

[BibT_eX]

[DOI]

Neural Networks, 1990

The Relationship Between Occam's Razor and Convergent Guessing.

[BibT_eX]

[DOI]

Complex Syst., 1990

A Mathematical Theory of Generalization: Part II.

[BibT_eX]

[DOI]

Complex Syst., 1990

A Mathematical Theory of Generalization: Part I.

[BibT_eX]

[DOI]