SUMMARY Stock trading is one of the key items in an economy and estimating its behavior and taking the best decision in it are among the most challenging issues. Solutions based on intelligent agent systems are proposed to cope with those challenges. Agents in a multiagent system (MAS) can share a common goal or they can pursue their own interests. That nature of MASs exactly fits the requirements of a free market economy. Although existing studies include noteworthy proposals on agent‐based market simulation and researchers discuss theoretical design issues of agent‐based stock exchange systems, unfortunately only a very few of the studies consider exact development and implementation of multiagent stock trading systems within the software engineering perspective and guides to the software engineers for constructing such software systems starting from scratch. To fill this gap, in this paper, we discuss the development of a multiagent‐based stock trading system by taking into consideration software design according to a well‐defined agent oriented software engineering methodology and implementation with a widely‐used MAS software development framework. Each participant in the system is first designed as belief–desire–intention agents with their facts, goals, and plans, and then belief–desire–intention reasoning and behavioral structure of the designed agents are implemented. Lessons learned during design and development within the software engineering perspective and evaluation of the implemented multiagent stock exchange system are also reported. Copyright © 2011 John Wiley & Sons, Ltd.
In peer-to-peer (P2P) video streaming systems, one of the most challenging parts is to schedule video data dissemination, that is, each peer should carefully select the partner(s) it receives video from and the partner(s) it sends data to. We believe that an agent-based partner selection approach may improve the quality of streaming by taking both autonomy and dynamic plan selection into account in a goal-oriented manner. In this study, a Belief-Desire-Intention agent architecture for partner selection in P2P video streaming systems is introduced. The major concern of our study is to exhibit how to select the best partner during video streaming session whilst maximizing the quality of video and minimizing delay and hop count. The effects and comparative results of executing proposed agent behaviours are evaluated in the study. The proposed autonomous agent-based approach also provides an infrastructure in which the best plan for the achievement of optimum streaming goal can be dynamically determined and executed at runtime. Experimental results of the implementation have revealed to us that both of the partner selection methods (with or without agents) manage to increase the video quality. However, the agent-based approach performs better in terms of received bitrate, delay and hop count during streaming.
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