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Proceedings of the Tenth InternationalWorkshop onProgramming Multi-Agent SystemsProMAS @ AAMAS 2012Organised byMehdi Dastani, Utrecht University, The NetherlandsBrian Logan, University of Nottingham, UKJomi F. Hübner, Federal University of Santa Catarina, BrazilHeld with The Eleventh International Conference on AutonomousAgents and Multiagent Systems (AAMAS 2012)June 5th, Valencia, Spain
PrefaceOver the last decade, the ProMAS workshop series has provided a venue forstate-of-the-art research in programming languages and tools for the developmentof multi-agent systems. ProMAS aims to address both theoretical andpractical issues related to developing and deploying multi-agent systems, andthe workshops have provided a forum for the discussion of techniques, concepts,requirements and principles central to multi-agent programming technology, includingthe theory and application of agent programming languages, the specification,verification and analysis of agent systems, and the implementation ofsocial structures in agent-based systems. Many of these concepts and techniqueshave subsequently found widespread application in agent programming platformsand systems.For the tenth edition of ProMAS, we are pleased to be able to present aprogramme of high quality papers covering a wide range of topics in multi-agentsystem programming languages, including language design and efficient implementation,agent communication and robot programming. We hope ProMAS2012 will continue the successful tradition of previous ProMAS workshops, incontributing to the design of programming languages and tools that are bothprincipled and at the same time practical for ‘industrial-strength’ multi-agentsystems development.ProMAS 2012 Workshop OrganizersMehdi DastaniBrian LoganJomi F. HübnerJune 2012
Page 4 and 5: OrganisationOrganising CommitteeMeh
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- Dealing with conflicts based on p
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5. Brooks, R. A. (1991) Intelligenc
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An Agent-Based Cognitive Robot Arch
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It has been argued that building ro
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EnvironmentHardwareLocal SoftwareC+
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a cognitive layer can connect as a
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can reliably be differentiated and
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4 ExperimentTo evaluate the feasibi
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learn or gain knowledge from experi
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A Programming Framework for Multi-A
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exchange and storage of tuples (key
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Although some success [13] [14] hav
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as well as important non-functional
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component plans have been instantia
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A in the example) can evaluate all
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1. robot-1 issues a Localization(ro
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ACKNOWLEDGMENTThis work has been su
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The code was analysed both objectiv
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a conversation is following. Additi
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the context of a communication-heav
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Table 1. Core Agent ProtocolsAgent
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statistically significant using an
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to the conversation and has a perfo
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principal reasons. Firstly, it is a
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2. Muldoon, C., O’Hare, G.M.P., C
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In the following section we will at
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DevelopmentProductionHuman Readabil
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will then evaluate this new format
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encoder, it is first checked if the
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nents themselves. However, since th
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optimized for this format feature s
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Java serialization and Jadex Binary
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10. P. Hoffman and F. Yergeau, “U
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Caching the results of previous que
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querying an agent’s beliefs and g
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or relative performance of each pla
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were run for 1.5 minutes; 1.5 minut
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Size N K n p c qry U c upd Update c
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epresentation. The cache simply act
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6 ConclusionWe presented an abstrac
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Typing Multi-Agent Programs in simp
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1 // agent ag02 iterations (" zero
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3.1 simpAL OverviewThe main inspira
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3.2 Typing Agents with Tasks and Ro
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Defining Agent Scripts in simpAL (F
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that sends a message to the receive
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* error: wrong type for the param v
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Given an organization model, it is
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Learning to Improve Agent Behaviour
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2.1 Agent Programming LanguagesAgen
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choosing actions is to find a good
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1 init module {2 knowledge{3 block(
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of a module. For example, to change
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if bel(on(X,Y), clear(X)), a-goal(c
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mance. Figure 2d shows the same A f
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the current percepts of the agent.
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Author IndexAbdel-Naby, S., 69Alelc
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