
Metalearning of Sequential Strategies
In this report we review memorybased metalearning as a tool for buildi...
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Meta reinforcement learning as task inference
Humans achieve efficient learning by relying on prior knowledge about th...
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Human DecisionMaking under Limited Time
Subjective expected utility theory assumes that decisionmakers possess ...
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Memory shapes time perception and intertemporal choices
There is a consensus that human and nonhuman subjects experience tempor...
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An Adversarial Interpretation of InformationTheoretic Bounded Rationality
Recently, there has been a growing interest in modeling planning with in...
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InformationTheoretic Bounded Rationality
Bounded rationality, that is, decisionmaking and planning under resourc...
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Belief Flows of Robust Online Learning
This paper introduces a new probabilistic model for online learning whic...
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Subjectivity, Bayesianism, and Causality
Bayesian probability theory is one of the most successful frameworks to ...
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A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
We propose a novel Bayesian approach to solve stochastic optimization pr...
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Information, Utility & Bounded Rationality
Perfectly rational decisionmakers maximize expected utility, but crucia...
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Generalized Thompson Sampling for Sequential DecisionMaking and Causal Inference
Recently, it has been shown how sampling actions from the predictive dis...
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Convergence of Bayesian Control Rule
Recently, new approaches to adaptive control have sought to reformulate ...
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A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes
Adaptive control problems are notoriously difficult to solve even in the...
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A conversion between utility and information
Rewards typically express desirabilities or preferences over a set of al...
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A Bayesian Rule for Adaptive Control based on Causal Interventions
Explaining adaptive behavior is a central problem in artificial intellig...
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Free Energy and the Generalized Optimality Equations for Sequential Decision Making
The free energy functional has recently been proposed as a variational p...
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Bayesian Causal Induction
Discovering causal relationships is a hard task, often hindered by the n...
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AI Safety Gridworlds
We present a suite of reinforcement learning environments illustrating v...
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Modeling Friends and Foes
How can one detect friendly and adversarial behavior from raw data? Dete...
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Intrinsic Social Motivation via Causal Influence in MultiAgent RL
We derive a new intrinsic social motivation for multiagent reinforcemen...
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Understanding Agent Incentives using Causal Influence Diagrams, Part I: Single Action Settings
Agents are systems that optimize an objective function in an environment...
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Social Influence as Intrinsic Motivation for MultiAgent Deep Reinforcement Learning
We propose a unified mechanism for achieving coordination and communicat...
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