By Joaquim Filipe, Ana Fred
This publication constitutes the completely refereed post-conference court cases of the fifth foreign convention on brokers and synthetic Intelligence, ICAART 2013, held in Barcelona, Spain, in February 2013. The 20 revised complete papers awarded including one invited paper have been rigorously reviewed and chosen from 269 submissions. The papers are geared up in topical sections on man made intelligence and on agents.
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Extra resources for Agents and Artificial Intelligence: 5th International Conference, ICAART 2013, Barcelona, Spain, February 15-18, 2013. Revised Selected Papers
M . Summarizing, in this model there are m decision makers (agents) ai , that pursue a common goal by each contributing one solution element wij from their associated local search space, while at the same time minimizing the resulting local penalty Πi (wij ). 28 C. Hinrichs et al. Obviously, if an agent ai changes its state σi , this should have an eﬀect on the decision making of the other agents in the system. Thus, the deﬁnition of how an arbitrary agent ak perceives a conﬁguration Σk , and how this relates to Σglobal , is crucial for solving the DO-MC-COP in a distributed way.
Nucl. Phys. B688, B691, 101–134, 129–181 (2004); B724, 3–182 (2005) 34. : Computer Go. Artif. Intell. 134(1–2), 145–179 (2002) 35. : Asymptotical properties of minimax trees and game searching procedures. Artif. Intell. 14(2), 113–138 (1980) 36. : Heuristics Intelligent Search Strategies for Computer Problem Solving. Addison-WesleyPublishing Co, Reading (1984) 37. : Best-First Fixed-Depth Minimax Algorithms. Artiﬁcial Intelligence 87(1–2), 255–293 (1996) 38. : Game-tree searching by min-max approximation.
002, respectively. f. Sect. 4), simulation ﬁtness improves signiﬁcantly. 04, respectively). 6 Population Size Another interesting property regarding real-world applications is the inﬂuence of population size on the heuristic. In Fig. 4(d), a linear increase in simulation steps until termination can be seen. This is consequently due to the increased coordination complexity in larger networks. Yet, since the increase is linear at most, this shows that COHDA is quite robust against the number of participating individuals.
Agents and Artificial Intelligence: 5th International Conference, ICAART 2013, Barcelona, Spain, February 15-18, 2013. Revised Selected Papers by Joaquim Filipe, Ana Fred