نتایج جستجو برای: rational agent
تعداد نتایج: 317205 فیلتر نتایج به سال:
I develop a framework in which a principal can exploit myopic social learning in a population of agents in order to implement social or selfish outcomes that would not be possible under the traditional fully-rational agent model. Learning in this framework takes a simple form of imitation, or replicator dynamics, a class of learning dynamics that often leads the population to converge to a Nash...
An algorithm for $n-1$-strong-equillibrium for distributed consensus in a ring with rational agents was proposed by Afek et al. (2014). A proof of impossibility of $n-1$-strong-equillibrium for distributed consensus in every topology with rational agents, when $n$ is even, is presented. Furthermore, we show that the algorithm proposed by Afek et al. is the only algorithm which can solve the pro...
We study infinitely repeated symmetric 2×2 games played by bounded rational agents who follow a simple rule of thumb: each agent continues to play the same action if the current payoff exceeds the average of the past payoffs, and switches to the other action with a positive probability otherwise. By applying the stochastic approximation technique, we characterize the asymptotic outcomes for all...
Contemporary approaches to inductive logic divide into two schools distinguished by how each perceives the investment of a rational agent in a given hypothesis. For the probabilist school, investments are degrees-of-belief, scattered over all the hypotheses in play. For advocates of Formal Learning Theory, an investment has a more absolute character, and is designated as \acceptance." The di er...
We analyze a model of learning and belief formation in networks in which agents follow Bayes rule yet they do not recall their history of past observations and cannot reason about how other agents’ beliefs are formed. They do so by making rational inferences about their observations which include a sequence of independent and identically distributed private signals as well as the beliefs of the...
An important problem faced by boundedly rational agents is to identify “regions of rationality,” i.e., the areas for which simple, boundedly rational models are and are not effective. To map the contours of such regions, we derive probabilities that models identify the best of m alternatives (m > 2) characterized by k attributes (k > 1). The models include a single variable (lexicographic), var...
Intentional theory is a rich sub-field of Artificial Intelligence that has led to different models of resource-bounded rational agents with varying success. This paper describes the important works on modeling intention and the theory behind them, focusing on how an agent with intentions can be implemented using the existing theory. It finds that while as a whole intentional modeling has had mu...
One of the best known approaches to the development of rational agents is the BDI (Belief-Desire-Intention) architecture. In this paper we propose a new framework, PRACTIONIST (PRACTIcal reasONIng sySTem), to support the development of BDI agents in Java (using JADE) with a Prolog belief base. In PRACTIONIST we adopt a goal-oriented approach with a clear separation between the deliberation and ...
We take institutions seriously as both a rational response to dilemmas in which agents found themselves and a frame to which later rational agents adapted their behaviour in turn. Medieval corporate bodies knew that they needed choice procedures. Although the social choice advances of ancient Greece and Rome were not rediscovered until the high middle ages, the rational design of choice institu...
Game theory is a tool for the analysis of the interaction among usually rational agents, the formulation of hypotheses about their behaviour and the prediction of the results of each interaction. From this standpoint it is very suitable for the analysis of environmental problems and for the definition of self-enforcing environmental agreements that are founded on cooperation and stability. With...
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