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Related papers: Information, Utility & Bounded Rationality

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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

A perfectly rational decision-maker chooses the best action with the highest utility gain from a set of possible actions. The optimality principles that describe such decision processes do not take into account the computational costs of…

Artificial Intelligence · Computer Science 2013-12-25 Jordi Grau-Moya , Daniel A. Braun

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

The free energy functional has recently been proposed as a variational principle for bounded rational decision-making, since it instantiates a natural trade-off between utility gains and information processing costs that can be…

Machine Learning · Statistics 2012-05-18 Pedro A. Ortega , Daniel A. Braun

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

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

A central challenge for intelligent agents in an uncertain world is striking the right balance between utility maximization and resource use, not only for external movement but also for internal computation. Existing theories of control…

Artificial Intelligence · Computer Science 2026-05-19 Itzel Olivos-Castillo , Paul Schrater , Xaq Pitkow

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

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e.…

Machine Learning · Statistics 2016-10-07 Pedro A. Ortega , Alan A. Stocker

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

Classic mechanism/information design imposes the assumption that agents are fully rational, meaning each of them always selects the action that maximizes her expected utility. Yet many empirical evidence suggests that human decisions may…

Computer Science and Game Theory · Computer Science 2023-11-14 Yiding Feng , Chien-Ju Ho , Wei Tang

Specialization and hierarchical organization are important features of efficient collaboration in economical, artificial, and biological systems. Here, we investigate the hypothesis that both features can be explained by the fact that each…

Multiagent Systems · Computer Science 2018-09-19 Sebastian Gottwald , Daniel A. Braun

We show how (resource) bounded rationality can be understood as the interplay of two fundamental moral principles: deontology and utilitarianism. In particular, we interpret deontology as a regularisation function in an optimal control…

Information Theory · Computer Science 2025-01-16 Roland M. Friedrich

Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that…

Machine Learning · Computer Science 2020-06-30 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

Active inference, a corollary of the free energy principle, is a formal way of describing the behavior of certain kinds of random dynamical systems that have the appearance of sentience. In this chapter, we describe how active inference…

Machine Learning · Statistics 2021-10-11 Noor Sajid , Lancelot Da Costa , Thomas Parr , Karl Friston

Many fairness criteria constrain the policy or choice of predictors, which can have unwanted consequences, in particular, when optimizing the policy under such constraints. Here, we advocate to instead focus on the utility function the…

Machine Learning · Statistics 2025-03-19 Frederik Hytting Jørgensen , Sebastian Weichwald , Jonas Peters

Data-driven decision making plays an important role even in high stakes settings like medicine and public policy. Learning optimal policies from observed data requires a careful formulation of the utility function whose expected value is…

Machine Learning · Statistics 2023-11-29 Eli Ben-Michael , Kosuke Imai , Zhichao Jiang

The tradeoff relation between speed and cost is a central issue in designing fast and efficient information processing devices. We derive an achievable bound on thermodynamic cost for obtaining information through finite-time…

Statistical Mechanics · Physics 2024-05-16 Rihito Nagase , Takahiro Sagawa

We review recent work on the foundations of thermodynamics in the light of quantum information theory. We adopt a resource-theoretic perspective, wherein thermodynamics is formulated as a theory of what agents can achieve under a particular…

Deviations from rational decision-making due to limited computational resources have been studied in the field of bounded rationality, originally proposed by Herbert Simon. There have been a number of different approaches to model bounded…

Artificial Intelligence · Computer Science 2015-11-06 Jordi Grau-Moya , Daniel A. Braun
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