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Using a novel toy nautical navigation environment, we show that dynamic programming can be used when only incomplete information about a partially observed Markov decision process (POMDP) is known. By incorporating uncertainty into our…

Optimization and Control · Mathematics 2022-07-20 Chris Beeler , Xinkai Li , Colin Bellinger , Mark Crowley , Maia Fraser , Isaac Tamblyn

Human dynamics is known to be inhomogeneous and bursty but the detailed understanding of the role of human factors in bursty dynamics is still lacking. In order to investigate their role we devise an agent-based model, where an agent in an…

Physics and Society · Physics 2012-01-06 Hang-Hyun Jo , Eunyoung Moon , Kimmo Kaski

We discuss representing and reasoning with knowledge about the time-dependent utility of an agent's actions. Time-dependent utility plays a crucial role in the interaction between computation and action under bounded resources. We present a…

Artificial Intelligence · Computer Science 2013-03-26 Eric J. Horvitz , Geoffrey Rutledge

During interactions with human consultants, people are used to providing partial and/or inaccurate information, and still be understood and assisted. We attempt to emulate this capability of human consultants; in computer consultation…

Artificial Intelligence · Computer Science 2013-03-26 Bhavani Raskutti , Ingrid Zukerman

By treating the financial market as a thermodynamic system, we establish a one-to-one correspondence between thermodynamic variables and economic quantities. Measured by the expected loss under the worst-case scenario, financial risk caused…

Risk Management · Quantitative Finance 2019-04-02 Yu Feng

The birth, life, and death of Maxwell's demon provoked a profound discussion about the interplay between thermodynamics, computation, and information. Even after its exorcism, the demon continues to inspire a multidisciplinary field. This…

Quantum Physics · Physics 2025-08-13 A. de Oliveira Junior , Jonatan Bohr Brask , Rafael Chaves

When human operators of cyber-physical systems encounter surprising behavior, they often consider multiple hypotheses that might explain it. In some cases, taking information-gathering actions such as additional measurements or control…

Artificial Intelligence · Computer Science 2024-11-22 Ofer Dagan , Tyler Becker , Zachary N. Sunberg

The dominant theories of rational choice assume logical omniscience. That is, they assume that when facing a decision problem, an agent can perform all relevant computations and determine the truth value of all relevant logical/mathematical…

Artificial Intelligence · Computer Science 2023-07-12 Caspar Oesterheld , Abram Demski , Vincent Conitzer

Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction and quantum metrology. Its use in the context of…

This paper focuses on designing expert systems to support decision making in complex, uncertain environments. In this context, our research indicates that strictly probabilistic representations, which enable the use of decision-theoretic…

Artificial Intelligence · Computer Science 2013-04-15 Samuel Holtzman , John S. Breese

Quantifying uncertainties in collective human behavior and decision making is crucial for ensuring public health and safety, enabling effective disaster response, informing the design of transportation and communication networks, and…

Physics and Society · Physics 2016-12-02 Kimberly J. Schlesinger , Chantal Nguyen , Imtiaz Ali , Jean M. Carlson

The thermodynamic uncertainty relation expresses a universal trade-off between precision and entropy production, which applies in its original formulation to current observables in steady-state systems. We generalize this relation to…

Statistical Mechanics · Physics 2018-12-06 Timur Koyuk , Udo Seifert , Patrick Pietzonka

Self-propulsion allows living systems to display unusual collective behavior. Unlike passive systems in thermal equilibrium, active matter systems are not constrained by conventional thermodynamic laws. A question arises however as to what…

Soft Condensed Matter · Physics 2015-03-18 Sho C. Takatori , John F. Brady

We study the design of autonomous agents that are capable of deceiving outside observers about their intentions while carrying out tasks in stochastic, complex environments. By modeling the agent's behavior as a Markov decision process, we…

Artificial Intelligence · Computer Science 2021-09-15 Yagiz Savas , Christos K. Verginis , Ufuk Topcu

Machines are being increasingly used in decision-making processes, resulting in the realization that decisions need explanations. Unfortunately, an increasing number of these deployed models are of a 'black-box' nature where the reasoning…

Artificial Intelligence · Computer Science 2023-11-07 Sopam Dasgupta

Networked multi-agent dynamical systems have been used to model how individual opinions evolve over time due to the opinions of other agents in the network. Particularly, such a model has been used to study how a planning agent can be used…

Social and Information Networks · Computer Science 2026-03-19 Sheryl Paul , Leslie Cruz Juarez , Jyotirmoy V. Deshmukh , Ketan Savla

Maxwell's demon was created with abilities to violate the second law of thermodynamics. But the demon always fell short of doing so because of the imposed restrictive condition that reads, the demon needs to do "work". Therefore, you can…

General Physics · Physics 2012-07-13 Andrew Das Arulsamy

In game theory and artificial intelligence, decision making models often involve maximizing expected utility, which does not respect ordinal invariance. In this paper, the author discusses the possibility of preserving ordinal invariance…

Artificial Intelligence · Computer Science 2010-06-14 Ji Han

Classical and quantum electronic circuits provide ideal platforms to investigate stochastic thermodynamics and they have served as a stepping stone to realize Maxwell's demons with highly controllable protocols. In this article we first…

Statistical Mechanics · Physics 2024-01-24 J. P. Pekola , I. M. Khaymovich

A primary motivation for reasoning under uncertainty is to derive decisions in the face of inconclusive evidence. However, Shafer's theory of belief functions, which explicitly represents the underconstrained nature of many reasoning…

Artificial Intelligence · Computer Science 2013-04-08 Thomas M. Strat