Advances in Agent Oriented Software Engineering have focused on the provision of frameworks and toolkits to aid in the creation of Multi Agent Systems (MASs). However, despite the need to address the inherent complexity of such systems, little progress has been made in the development of tools to allow for the debugging and understanding of their inner workings. This paper introduces a novel performance analysis system, named AgentSpotter, which facilitates such analysis. AgentSpotter was developed by mapping conventional profiling concepts to the domain of MASs. We outline its integration into the Agent Factory multi agent framework.
The Brahms toolkit features an AgentViewer that allows developers to view along a time line the actions that particular agents have taken, so as to enable them to verify that the conceptual model of the MAS is reflected in reality @cite_1 . An administrator tool for the LS TS agent platform provides some high-level system monitoring information, such as overall memory consumption and data on the size of the agent population @cite_0 . Another type of agent debugging tool is the ACLAnalyzer that has been developed for the JADE platform @cite_5 . Rather than concentrating on individual agents, it is intended to analyse agent interaction in order to see how the community of agents interacts and is organised. In addition to visualising the number and size of messages sent between specific agents, it also employs clustering in order to identify cliques in the agent community.
@cite_0 @cite_5 @cite_1
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The JADE Platform and Experiences with Mobile MAS Applications.- A-globe: Agent Development Platform with Inaccessibility and Mobility Support.- Supporting Agent Development in Erlang through the eXAT Platform.- Living Systems(R) Technology Suite.- Multi Agent System Development Kit.- An Integrated Development Environment for Electronic Institutions.- Jadex: A BDI-Agent System Combining Middleware and Reasoning.- Component Agent Framework for Non-Experts (CAFnE) Toolkit.- The WSDL2Agent Tool.- WS2JADE: A Tool for Run-time Deployment and Control of Web Services as JADE Agent Services.- A System for Analysis of Multi-Issue Negotiation.- FuzzyMAN: An Agent-based E-Marketplace with a Voice and Mobile User Interface.- Efficient Agent Communication in Wireless Environments.- AMETAS - the Asynchronous MEssage Transfer Agent System.- Tracy: An Extensible Plugin-Oriented Software Architecture for Mobile Agent Toolkits.- The Packet-World: A Test Bed for Investigating Situated Multi-Agent Systems.- Decommitment in a Competitive Multi-Agent Transportation Setting.- TeamWorker: An Agent-Based Support System for Mobile Task Execution. This paper considers the basic PULL model of communication, in which in each round, each agent extracts information from few randomly chosen agents. We seek to identify the smallest amount of information revealed in each interaction (message size) that nevertheless allows for efficient and robust computations of fundamental information dissemination tasks. We focus on the Majority Bit Dissemination problem that considers a population of n agents, with a designated subset of source agents. Each source agent holds an input bit and each agent holds an output bit. The goal is to let all agents converge their output bits on the most frequent input bit of the sources (the majority bit). Note that the particular case of a single source agent corresponds to the classical problem of Broadcast (also termed Rumor Spreading). We concentrate on the severe fault-tolerant context of self-stabilization, in which a correct configuration must be reached eventually, despite all agents starting the execution with arbitrary initial states. In particular, the specification of who is a source and what is its initial input bit may be set by an adversary. We first design a general compiler which can essentially transform any self-stabilizing algorithm with a certain property (called "the bitwise-independence property") that uses l-bits messages to one that uses only log l-bits messages, while paying only a small penalty in the running time. By applying this compiler recursively we then obtain a self-stabilizing Clock Synchronization protocol, in which agents synchronize their clocks modulo some given integer T, within O(log n log T) rounds w.h.p., and using messages that contain 3 bits only. We then employ the new Clock Synchronization tool to obtain a self-stabilizing Majority Bit Dissemination protocol which converges in O(log n) time, w.h.p., on every initial configuration, provided that the ratio of sources supporting the minority opinion is bounded away from half. Moreover, this protocol also uses only 3 bits per interaction. In this paper, we present a method for inferring social roles of agents (persons) from their daily activities in long surveillance video sequences. We define activities as interactions between an agent's position and semantic hotspots within the scene. Given a surveillance video, our method first tracks the locations of agents then automatically discovers semantic hotspots in the scene. By enumerating spatial temporal locations between an agent's feet and hotspots in a scene, we define a set of atomic actions, which in turn compose sub-events and events. The numbers and types of events performed by an agent are assumed to be driven by his her social role. With the grammar model induced by composition rules, an adapted Earley parser algorithm is used to parse the trajectories into events, sub-events and atomic actions. With probabilistic output of events, the roles of agents can be predicted under the Bayesian inference framework. Experiments are carried out on a challenging 8.5 hours video from a surveillance camera in the lobby of a research lab. The video contains 7 different social roles including “manager”, “researcher”, “developer”, “engineer”, “staff”, “visitor” and “mailman”. Results show that our proposed method can predict the role of each agent with high precision. The ability to effectively debug agent-oriented applications is vital if agent technologies are to become adopted as a viable alternative for complex systems development. Recent advances in the area have focussed on the provision of support for debugging agent interaction where tools have been provided that allow developers to analyse and debug the messages that are passed between agents. One potential approach for constructing agent-oriented applications is through the use of agent programming languages. Such languages employ mental notions such as beliefs, goals, commitments, and intentions to facilitate the construction of agent programs that specify the high-level behaviour of the agent. This paper describes how debugging has been supported for one such language, namely the Agent Factory Agent Programming Language (AFAPL).