Planning agents in JAMES

被引:32
|
作者
Schattenberg, B [1 ]
Uhrmacher, AM
机构
[1] Univ Ulm, Fac Comp Sci, D-18059 Rostock, Germany
[2] Univ Ulm, Dept Comp Sci, D-18059 Rostock, Germany
关键词
multiagent systems; planning; simulation; test beds; testing;
D O I
10.1109/5.910852
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Testing is an obligatory step in developing multiagent systems. For testing multiagent systems in virtual, dynamic environments, simulation systems are required that support a modular, declarative construction of experimental frames, that facilitate the embeddence of a variety of agent architectures and that allow an efficient parallel, distributed execution. We introduce the system JAMES (A Java-based agent modeling environment for simulation). In JAMES, agents and their dynamic environment are modeled as reflective, time-triggered state automata. its possibilities to compose experimental frames based on predefined components, to express temporal, interdependencies, to capture the phenomenon of proactiveness and reflectivity of agents are illuminated by experiments with planning agents. The underlying planning system is a general-purpose pose system, about which no empirical results exist besides traditional static benchmark tests. We analyze the interplay between heuristics for selecting goals, viewing range, commitment strategies, explorativeness, and trust in the persistence of the world and uncover properties of the agent, the planning engine, and the chosen test scenario: TILEWORLD.
引用
收藏
页码:158 / 173
页数:16
相关论文
共 50 条
  • [21] Planning Rational Behavior of Cognitive Semiotic Agents in a Dynamic Environment
    G. S. Osipov
    A. I. Panov
    Scientific and Technical Information Processing, 2021, 48 : 502 - 516
  • [22] The logical foundations of goal-regression planning in autonomous agents
    Pollock, JL
    ARTIFICIAL INTELLIGENCE, 1998, 106 (02) : 267 - 334
  • [23] A genetic planner for mission planning of cooperative agents in an underwater environment
    Miloradovic, Branko
    Curuklu, Baran
    Ekstrom, Mikael
    PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016,
  • [24] The strategy for planning the future of a Christian believer in the exegetical context of James 4:13-15
    Pruzinsky, Stefan
    Kuzysin, Bohuslav
    Sip, Maros
    Kubicova, Anna
    Pruzinsky, Stefan
    HTS TEOLOGIESE STUDIES-THEOLOGICAL STUDIES, 2021, 77 (01):
  • [25] A better-response strategy for self-interested planning agents
    Jaume Jordán
    Alejandro Torreño
    Mathijs de Weerdt
    Eva Onaindia
    Applied Intelligence, 2018, 48 : 1020 - 1040
  • [26] Advanced Iterative Action Planning for Intelligent Real-Time Agents
    Panteleev, M. G.
    PROCEEDINGS OF THE 13TH INTERNATIONAL SYMPOSIUM INTELLIGENT SYSTEMS 2018 (INTELS'18), 2019, 150 : 244 - 252
  • [27] Topology-preserving flocking of nonlinear agents using optimistic planning
    Buşoniu L.
    Morărescu I.-C.
    Control Theory and Technology, 2015, 13 (1) : 70 - 81
  • [28] Learning time planning in a distance learning system using intelligent agents
    Kamsa, Imane
    Elouahbi, Rachid
    El Khoukhi, Fatima
    Elghibari, Fatiha
    Chehbi, Sanae
    2015 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY BASED HIGHER EDUCATION AND TRAINING (ITHET), 2015,
  • [29] Study of the performance of multi-behaviour agents for supply chain planning
    Forget, Pascal
    D'Amours, Sophie
    Frayret, Jean-Marc
    Gaudreault, Jonathan
    COMPUTERS IN INDUSTRY, 2009, 60 (09) : 698 - 708
  • [30] Topology-preserving flocking of nonlinear agents using optimistic planning
    Lucian BU?ONIU
    Irinel-Constantin MORRESCU
    Control Theory and Technology, 2015, 13 (01) : 70 - 81