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  Browse All Reviews > Computing Methodologies (I) > Artificial Intelligence (I.2) > Distributed Artificial Intelligence (I.2.11) > Multiagent Systems (I.2.11...)  
 
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  1-10 of 162 Reviews about "Multiagent Systems (I.2.11...)": Date Reviewed
  Markov chain aggregation for agent-based models
Banisch S.,  Springer International Publishing, New York, NY, 2015. 195 pp. Type: Book (978-3-319248-75-2)

Most techniques for modeling dynamic systems fall into one of two categories. Equation-based models such as system dynamics and other differential equation formalisms seek a closed-form expression for the overall dynamics, but typically characteri...

Jul 12 2017
  Computational models of motivation for game-playing agents
Merrick K.,  Springer International Publishing, New York, NY, 2016. 213 pp. Type: Book (978-3-319334-57-8)

One of the major dimensions in which current computer models of players in a gaming system differ from actual human players is affective aspects. Creating a computational model of motivation that can be implemented in such computer players blurs t...

Jun 22 2017
  Optimizing transport logistics processes with multiagent planning and control
Gath M.,  Springer Vieweg, Wiesbaden, Germany, 2016. 279 pp. Type: Book (978-3-658140-02-1)

Modern logistics brings various challenging and complex problems to researchers’ attention. Among them, planning and control problems need efficient problem-solving approaches; multiagent systems are known as the most state-of-the-art artifi...

Apr 26 2017
  Multiagent resource allocation for dynamic task arrivals with preemption
Doucette J., Pinhey G., Cohen R.  ACM Transactions on Intelligent Systems and Technology 8(1): 1-27, 2016. Type: Article

The authors describe a new approach to multiagent resource allocation problems. A typical problem would be the allocation of resources in an emergency room situation as new cases arrive continually. The model consists of four components: tasks, ta...

Sep 15 2016
  Agent-based modelling in economics
Hamill L., Gilbert N.,  Wiley Publishing, Chichester, UK, 2016. 256 pp. Type: Book (978-1-118456-07-1)

The social sciences have long been plagued by physics envy. The seductive simplicity of closed-form equations with strong predictive power in dealing with billiard balls, planets, and electrons suggests that we ought to be able to analyze the beha...

Aug 25 2016
  Artificial intelligence applications in information and communication technologies
Laalaoui Y., Bouguila N.,  Springer International Publishing, New York, NY, 2015. 213 pp. Type: Book (978-3-319198-32-3)

According to analysts, data volumes are expected to grow 44 fold in a decade (2011-2020). The variety of the data, along with the speed with which it is generated in an increasingly connected world, makes artificial intelligence (AI)-driven soluti...

Jul 8 2016
  Exponential moving average based multiagent reinforcement learning algorithms
Awheda M., Schwartz H.  Artificial Intelligence Review 45(3): 299-332, 2016. Type: Article

Reinforcement learning for multiagent systems aims to find optimal policies that can be learned by agents during their interaction in cooperative or competitive games. In game theory, the target is reaching the Nash equilibrium, where each agent i...

Jun 15 2016
  General tiebreaking schemes for computational social choice
Freeman R., Brill M., Conitzer V.  AAMAS 2015 (Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, Istanbul, Turkey,  May 4-8, 2015) 1401-1409, 2015. Type: Proceedings

Tiebreaking is a natural issue in social choice and in computational social choice. However, with the passing of time, it has become more and more clear that tiebreaking is a quite important and subtle issue, and that in some cases one’s cho...

May 23 2016
  Formation and containment control for high-order linear swarm systems
Dong X.,  Springer Publishing Company, Incorporated, New York, NY, 2015. 170 pp. Type: Book (978-3-662478-35-6)

This is an interesting book published as a version of a PhD thesis. It focuses on the analytics of fundamental aspects of swarm robots modeled as multiagent systems, where individual and collective behaviors of the swarms play key roles in the suc...

Apr 26 2016
  Search and tracking algorithms for swarms of robots
Senanayake M., Senthooran I., Barca J., Chung H., Kamruzzaman J., Murshed M.  Robotics and Autonomous Systems 75, Part B, 422-434, 2016. Type: Article

Swarm intelligence (SI) systems exploit artificial or physical agents to solve optimization tasks without the need for a supervisor. Can swarm robots benefit from SI? To answer, this paper surveys how the search-and-tracking problem can be solved ...

Mar 8 2016
 
 
 
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