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Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we propose an information-theoretic formalization of bounded rational decision-making…

Statistics Theory · Mathematics 2015-06-04 Pedro A. Ortega , Daniel A. Braun

Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we employ an axiomatic framework for bounded rational decision-making based on a…

Artificial Intelligence · Computer Science 2011-07-29 Pedro A. Ortega , Daniel A. Braun

When robots share the same workspace with other intelligent agents (e.g., other robots or humans), they must be able to reason about the behaviors of their neighboring agents while accomplishing the designated tasks. In practice,…

Robotics · Computer Science 2022-10-18 Junhong Xu , Durgakant Pushp , Kai Yin , Lantao Liu

Making decisions freely presupposes that there is some indeterminacy in the environment and in the decision making engine. The former is reflected on the behavioral changes due to communicating: few changes indicate rigid environments;…

Artificial Intelligence · Computer Science 2020-09-23 Luis A. Pineda

Rationality is frequently associated with making the best possible decisions. It's widely acknowledged that humans, as rational beings, have limitations in their decision-making capabilities. Nevertheless, recent advancements in fields,…

Computers and Society · Computer Science 2023-11-03 Dibakar Das

Rationality is often related to optimal decision making. Humans are known to be bounded rational agents. However, recent advances in computing, and other scientific and technical fields along with large amount of data have led to a feeling…

Computers and Society · Computer Science 2023-06-21 Dibakar Das

An agent choosing between various actions tends to take the one with the lowest cost. But this choice is arguably too rigid (not adaptive) to be useful in complex situations, e.g., where exploration-exploitation trade-off is relevant in…

Data Analysis, Statistics and Probability · Physics 2018-12-04 Armen E. Allahverdyan , Aram Galstyan , Ali E. Abbas , Zbigniew R. Struzik

Bounded rationality, that is, decision-making and planning under resource limitations, is widely regarded as an important open problem in artificial intelligence, reinforcement learning, computational neuroscience and economics. This paper…

Machine Learning · Statistics 2015-12-22 Pedro A. Ortega , Daniel A. Braun , Justin Dyer , Kee-Eung Kim , Naftali Tishby

Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete…

Artificial Intelligence · Computer Science 2013-04-11 Eric J. Horvitz

Recently, there has been a growing interest in modeling planning with information constraints. Accordingly, an agent maximizes a regularized expected utility known as the free energy, where the regularizer is given by the information…

Artificial Intelligence · Computer Science 2014-09-24 Pedro A. Ortega , Daniel D. Lee

We develop a novel framework of bounded rationality under cognitive frictions that studies learning over optimal behavior through both deliberative reasoning and accumulated experiences. Using both types of information, agents engage in…

Theoretical Economics · Economics 2024-03-28 Cosmin Ilut , Rosen Valchev

Classic decision-theory is based on the maximum expected utility (MEU) principle, but crucially ignores the resource costs incurred when determining optimal decisions. Here we propose an axiomatic framework for bounded decision-making that…

Artificial Intelligence · Computer Science 2010-07-09 Pedro A. Ortega , Daniel A. Braun

A sequential decision-making agent balances between exploring to gain new knowledge about an environment and exploiting current knowledge to maximize immediate reward. For environments studied in the traditional literature, optimal…

Machine Learning · Computer Science 2024-07-23 Dilip Arumugam , Wanqiao Xu , Benjamin Van Roy

The study of intelligent systems explains behaviour in terms of economic rationality. This results in an optimization principle involving a function or utility, which states that the system will evolve until the configuration of maximum…

Information Theory · Computer Science 2024-06-18 Pedro Hack

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

Rational decision making in its linguistic description means making logical decisions. In essence, a rational agent optimally processes all relevant information to achieve its goal. Rationality has two elements and these are the use of…

Artificial Intelligence · Computer Science 2019-02-14 Tshilidzi Marwala

General criterion for best efficiency of the interaction of a complex system with an ever-changing environment is derived. Its exclusive property, set by boundedness, is that the highly non-trivial interplay between parameters that…

Adaptation and Self-Organizing Systems · Physics 2014-03-12 Maria K. Koleva

In this paper the theory of flexibly-bounded rationality which is an extension to the theory of bounded rationality is revisited. Rational decision making involves using information which is almost always imperfect and incomplete together…

Artificial Intelligence · Computer Science 2013-06-11 Tshilidzi Marwala

Bounded rationality investigates utility-optimizing decision-makers with limited information-processing power. In particular, information theoretic bounded rationality models formalize resource constraints abstractly in terms of relative…

Artificial Intelligence · Computer Science 2018-09-07 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

The emergent behavior of a distributed system is conditioned by the information available to the local decision-makers. Therefore, one may expect that providing decision-makers with more information will improve system performance; in this…

Computer Science and Game Theory · Computer Science 2023-06-23 Bryce L. Ferguson , Dario Paccagnan , Jason R. Marden
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