Here - Agents Lab - University of Nottingham

Recommendations

Info

decisions taken during the design and implementation phases, such as e.g. theuse of the ERESYE tool during an early stage and its later replacement.Clearly, the similarities between the capabilities of agents and the Erlangprocesses are many, with the exception of the support for programming rationalreasoning in Jason. We believe that the existence of eJason can help attract Erlangprogrammers to the MAS community, by providing them a convenient andlargely familiar platform in which to program rational agents, while being ableto implement the rest (adapting interpreter meta behaviour, and actuators forthe environment) in Erlang itself. Moreover we believe that the MAS communitycan benefit from having access to the efficient concurrency and distribution capabilitiesof Erlang, while maintaining backward compatibility with legacy code,and without the need to develop a new agent-based language.Clearly, as eJason is still a prototype, there are numerous areas for futurework and improvement. The subset of Jason implemented at the moment is quitesmall; it is, for example, necessary to add support for belief annotations and planlabeling. Moreover, we plan to add support in eJason for different distributedagent architectures. An essential item for near future work is the implementationof a means for agents to act on their environment. We intend to make eJasonagents capable to cause changes in their environment using actions programmedeither in Java or Erlang, i.e., there should be no need to rewrite the large bodyof existing Java code for Jason environment handling. Besides, we expect to beable to use the agent inspection mechanisms already implemented in e.g. JEdit.Another item for future work includes prototyping extensions to Jason; webelieve that eJason is a good platform on which to perform such experiments. Finallywe also intend to experiment with model checking, applied on the resultingErlang code, to verify Jason multiagent systems.References1. Foundation for Intelligent Physical Agents, Agent Communication Language.http://www.fipa.org/specs/fipa00061/SC00061G.html.2. Simple Agent Communication Infrastructure. See: http://www.lti.pcs.usp.br/saci/.3. Joe Armstrong. Programming Erlang: Software for a concurrent world). ThePragmatic Bookshelf, 2007.4. Joe Armstrong, Robert Virding, and Mike Williams. Use of Prolog for developinga new programming language. In Proc. of the international conference on PracticalApplication of Prolog, 1992.5. Fabio Bellifemine, Federico Bergenti, Giovanni Caire, and Agostino Poggi. JADE- a Java agent development framework. In Rafael H. Bordini, Mehdi Dastani,Jürgen Dix, and Amal El Fallah-Seghrouchni, editors, Multi-Agent Programming,volume 15 of Multiagent Systems, Artificial Societies, and Simulated Organizations,pages 125–147. Springer, 2005.6. Fabio L. Bellifemine, Giovanni Caire, and Dominic Greenwood. Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology). Wiley, April 2007.7. R. Bordini and J. Hübner. Bdi agent programming in agentspeak using jason.Computational logic in multi-agent systems, pages 143–164, 2006.21
8. Rafael H. Bordini, Michael Fisher, Willem Visser, and Michael Wooldridge. Verifyingmulti-agent programs by model checking. Journal of Autonomous Agentsand Multi-Agent Systems, 12:2006, 2006.9. Rafael H. Bordini, Michael Wooldridge, and Jomi Fred Hübner. ProgrammingMulti-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology).John Wiley & Sons, 2007.10. F. Cesarini and S. Thompson. Erlang Programming. O’Reilly Media, 2009.11. J.F. Hübner. Um modelo de reorganização de sistemas multiagentes [In Portuguese].PhD thesis, Universidade de São Paulo, Escola Politécnica, Brazil, 2003.12. P. D. O’Brien and R. C. Nicol. FIPA - Towards a Standard for Software Agents.BT Technology Journal, 16:51–59, July 1998.13. Anand S. Rao. AgentSpeak(L): BDI agents speak out in a logical computablelanguage. In Walter Van de Velde and John W. Perram, editors, Agents BreakingAway, volume 1038 of LNCS, pages 42–55. Springer, 1996. 7th European Workshopon Modelling Autonomous Agents in a Multi-Agent World (MAAMAW’96),Eindhoven, The Netherlands, 22-25 January 1996, Proceedings.14. Anand S. Rao and Michael P. Georgeff. BDI agents: From theory to practice. In InProceedings of the first Interntional Conference on Multi-Agent Systems (ICMAS-95, pages 312–319, 1995.15. Antonella Di Stefano, Francesca Gangemi, and Corrado Santoro. ERESYE: artificialintelligence in erlang programs. In Konstantinos F. Sagonas and Joe Armstrong,editors, Erlang Workshop, pages 62–71. ACM, 2005.16. M. Wooldridge and N.R. Jennings. Intelligent agents: Theory and practice. Knowledgeengineering review, 10(2):115–152, 1995.17. Michael Wooldridge. Reasoning about rational agents. MIT Press, 2000.22
Page 2 and 3: Proceedings of the Tenth Internatio
Page 4 and 5: OrganisationOrganising CommitteeMeh
Page 6: Table of ContentseJason: an impleme
Page 10 and 11: in Sect. 3 the translation of the J
Page 12 and 13: init_count(0).max_count(2000).(a)(b
Page 14 and 15: For instance, a failure in the ERES
Page 16 and 17: {plan, fun start_count_trigger/1,fu
Page 18 and 19: single parameter, an Erlang record
Page 20 and 21: 1. Belief annotations. Even though
Page 24 and 25: Conceptual Integration of Agents wi
Page 26 and 27: Fig. 2. Active component structurep
Page 28 and 29: the service provider component. As
Page 30 and 31: Fig. 4. Web Service Invocationretri
Page 32 and 33: 01: public interface IBankingServic
Page 34 and 35: tate them in the same way as in the
Page 36 and 37: 01: public interface IChartService
Page 38 and 39: implementations being available for
Page 41: deliberative behavior in BDI archit
Page 44 and 45: layer modules (i.e. nodes) can be d
Page 46 and 47: different methods to choose the cur
Page 48 and 49: also a single scheduler module, imp
Page 50 and 51: andom choice (OR), conditional choi
Page 52 and 53: - Dealing with conflicts based on p
Page 54 and 55: 5. Brooks, R. A. (1991) Intelligenc
Page 56 and 57: An Agent-Based Cognitive Robot Arch
Page 58 and 59: It has been argued that building ro
Page 60 and 61: EnvironmentHardwareLocal SoftwareC+
Page 62 and 63: a cognitive layer can connect as a
Page 64 and 65: can reliably be differentiated and
Page 66 and 67: 4 ExperimentTo evaluate the feasibi
Page 68 and 69: learn or gain knowledge from experi
Page 70 and 71: A Programming Framework for Multi-A
Page 72 and 73:
exchange and storage of tuples (key
Page 74 and 75:
Although some success [13] [14] hav
Page 76 and 77:
as well as important non-functional
Page 78 and 79:
component plans have been instantia
Page 80 and 81:
A in the example) can evaluate all
Page 83 and 84:
1. robot-1 issues a Localization(ro
Page 85 and 86:
ACKNOWLEDGMENTThis work has been su
Page 87 and 88:
The code was analysed both objectiv
Page 89 and 90:
a conversation is following. Additi
Page 91 and 92:
the context of a communication-heav
Page 93 and 94:
Table 1. Core Agent ProtocolsAgent
Page 95 and 96:
statistically significant using an
Page 97 and 98:
to the conversation and has a perfo
Page 99 and 100:
principal reasons. Firstly, it is a
Page 101 and 102:
2. Muldoon, C., O’Hare, G.M.P., C
Page 103 and 104:
In the following section we will at
Page 105 and 106:
DevelopmentProductionHuman Readabil
Page 107 and 108:
will then evaluate this new format
Page 109 and 110:
encoder, it is first checked if the
Page 111 and 112:
nents themselves. However, since th
Page 113 and 114:
optimized for this format feature s
Page 115 and 116:
Java serialization and Jadex Binary
Page 117 and 118:
10. P. Hoffman and F. Yergeau, “U
Page 119 and 120:
Caching the results of previous que
Page 121 and 122:
querying an agent’s beliefs and g
Page 123 and 124:
or relative performance of each pla
Page 125 and 126:
were run for 1.5 minutes; 1.5 minut
Page 127 and 128:
Size N K n p c qry U c upd Update c
Page 129 and 130:
epresentation. The cache simply act
Page 131 and 132:
6 ConclusionWe presented an abstrac
Page 133 and 134:
Typing Multi-Agent Programs in simp
Page 135 and 136:
1 // agent ag02 iterations (" zero
Page 137 and 138:
3.1 simpAL OverviewThe main inspira
Page 139 and 140:
3.2 Typing Agents with Tasks and Ro
Page 141 and 142:
Defining Agent Scripts in simpAL (F
Page 143 and 144:
that sends a message to the receive
Page 145 and 146:
* error: wrong type for the param v
Page 147 and 148:
Given an organization model, it is
Page 149 and 150:
Learning to Improve Agent Behaviour
Page 151 and 152:
2.1 Agent Programming LanguagesAgen
Page 153 and 154:
choosing actions is to find a good
Page 155 and 156:
1 init module {2 knowledge{3 block(
Page 157 and 158:
of a module. For example, to change
Page 159 and 160:
if bel(on(X,Y), clear(X)), a-goal(c
Page 161 and 162:
mance. Figure 2d shows the same A f
Page 163 and 164:
the current percepts of the agent.
Page 165:
Author IndexAbdel-Naby, S., 69Alelc
show all

Here - Agents Lab - University of Nottingham

Create successful ePaper yourself

Delete template?

Save as template?