Search results

...n and [[decision-making]] among multiple agents. It is a [[probabilistic]] model that can consider [[uncertainty]] in outcomes, sensors and communication (i * <math>A_i</math> is a set of actions for agent <math>i</math>, with <math>A=\times_i A_i</math> is the set of joint action ...

...s a formalization of decentralized or distributed systems of [[Intelligent agent|agents]] in [[artificial intelligence]].<ref name="gramsysdis">{{cite thesi Let <math>\mathbb{A}</math> be a simple [[reactive agent]] moving on the table and trying not to fall down from the table with two r ...

...ence its environment.<ref name=klyubin2005a /><ref name=klyubin2005b /> An agent which follows an empowerment maximising policy, acts to maximise future opt ...the [[Motor cognition#Perception-action coupling|perception-action loop]]. Agent state and actions are modelled by random variables (<math>S: s \in \mathcal ...

...within its ''environment''. This knowledge is usually represented in logic-based [[action description language]] and used as the input for [[automated plann Learning action models is important when goals change. When an agent acted for a while, it can use its accumulated knowledge about actions in th ...

'''Inverse Planning''' refers to the process of inferring an agent's mental states, such as goals, beliefs, emotions, etc., from actions by as ...nverse Reinforcement Learning]], which attempts to learn a reward function based on agents' behavior, and [[Activity recognition|plan recognition]], which f ...

...rithm which was developed in 2002.<ref name="xzy02sco"/> This algorithm is based on the [[social cognitive theory]], and the key point of the ergodicity is ...cognitive agents solving in parallel, with a social sharing library. Each agent holds a private memory containing one knowledge point, and the social shari ...

...there is an additive [[errors and residuals|response error]]. Then for an agent <math> t \in T </math> , ...> \beta </math> which characterizes the effect of different factors on the agent's choice. ...

{{short description|Agent-based segregation model}} ...rst=Junfu | title=Tipping and residential segregation: a unified Schelling model | journal=Journal of Regional Science | publisher=Wiley | volume=51 | issue ...

...ors; take their action based on their prior belief and update their belief based on the history of the game.<ref>Song Y. and M. van der Schaar (2015) “Dynam ...ximates the distribution over a neighbors' degree from the [[configuration model]] with respect to a [[Degree (graph theory)|degree sequence]] represented b ...

...en two opposing strategies. Exploitation involves choosing the best option based on current knowledge of the system (which may be incomplete or misleading), ...(2nd edition). http://incompleteideas.net/book/the-book-2nd.html</ref> The agent must decide whether to exploit the current best-known policy or explore new ...

...d model of an [[exchange economy]] in [[microeconomics]], and the standard model of a game in [[game theory]]. An ''equilibrium'' in an abstract economy gen ...Walrasian equilibrium (aka competitive equilibrium) in the [[Arrow–Debreu model]].<ref name=":1">{{Cite journal|last1=Arrow|first1=Kenneth J.|last2=Debreu| ...

...ves a negative reward at every time step when the goal is not reached; the agent has no information about the goal until an initial success. ...ew Moore's PhD thesis (1990).<ref>[Moore, 1990] A. Moore, Efficient Memory-Based Learning for Robot Control, PhD thesis, University of Cambridge, November 1 ...

...[Blackwell's informativeness theorem#Garbling|informativeness]]'', and one based in ''[[Blackwell's informativeness theorem#Feasibility|feasibility]]''. Thi ...di |last2=Safra |first2=Zvi |author1-link=Edi Karni |title=Hybrid decision model and the ranking of experiments |journal=Journal of Mathematical Economics | ...

== Model == There are ''n'' agents. Each agent has a function that attributes a numeric value to each "bundle" (combinatio ...

In the standard consumer utility maximization problem of the [[economic agent]], she maximizes utility by consuming goods. In making an optimal consumpti ...g constraint.<ref>Nakajima, Makoto, 2007. "Note on the Heterogeneous Agent Model: Aiyagari (1994)" [http://www.compmacro.com/makoto/note/note_im_aiyagari.pd ...

...-4076(75)90032-9 |title=Maximum score estimation of the stochastic utility model of choice |date=1975 |last1=Manski |first1=Charles F. |journal=Journal of E ...able. Given that state, the agent behaves rationally. In other words: each agent has, not a single preference-relation, but a [[Probability distribution|''d ...

...nd of [[algorithmic pricing]] in which a seller determines the sell-prices based on probabilistic assumptions on the valuations of the buyers. It is a simpl ...rtunately, the seller does not know the buyer's valuation. In the Bayesian model, it is assumed that the buyer's valuation is a [[random variable]] drawn fr ...

...|date=1975-08-01 |title=Maximum score estimation of the stochastic utility model of choice |url=https://dx.doi.org/10.1016/0304-4076%2875%2990032-9 |journal ...able. Given that state, the agent behaves rationally. In other words: each agent has, not a single preference-relation, but a [[Probability distribution|''d ...

...delivered in June 1986. The first of the significantly redesign production model, the PC-Warp, was delivered by G.E. in April 1987. About twenty production One PE consists of two main agents: a Computation Agent and a Communication Agent.<ref>{{Cite journal |last1=Borkar |first1=S. |last2=Cohn |first2=R. |last3= ...

...l randomized truthful mechanism for [[fair cake-cutting]]: select a single agent uniformly at random, and give him/her the entire cake. This mechanism is tr ...us division'') is a partition of the cake into ''n'' pieces such that each agent values each piece at exactly 1/''n''. The existence of such a division is [ ...