tailieunhanh - Lecture Multiagent systems - Chapter 10: Methodologies

Chapter 10 give an overview of work that has been carried out on the development of methodologies for multiagent systems. This work is, at the time of writing, rather tentative - not much experience has yet been gained with them. This chapter begin by considering some of the domain attributes that indicate the appropriateness of an agent-based solution. I then go on to describe various prototypical methodologies, and discuss some of the pitfalls associated with agent-oriented development. | LECTURE 10: Methodologies An Introduction to MultiAgent Systems Pitfalls of Agent Development Lots of (single and multi-) agent projects but agent-oriented development received little attention We now consider pragmatics of AO software projects Identifies key pitfalls Seven categories: political management conceptual analysis and design micro (agent) level macro (society) level implementation 10- You Oversell Agents Agents are not magic! If you can’t do it with ordinary software, you probably can’t do it with agents No evidence that any system developed using agent technology could not have been built just as easily using non-agent techniques Agents may make it easier to solve certain classes of problems but they do not make the impossible possible Agents are not AI by a back door Don’t equate agents and AI 10- You Get Religious Agents have been used in a wide range of applications, but they are not a universal solution For many . | LECTURE 10: Methodologies An Introduction to MultiAgent Systems Pitfalls of Agent Development Lots of (single and multi-) agent projects but agent-oriented development received little attention We now consider pragmatics of AO software projects Identifies key pitfalls Seven categories: political management conceptual analysis and design micro (agent) level macro (society) level implementation 10- You Oversell Agents Agents are not magic! If you can’t do it with ordinary software, you probably can’t do it with agents No evidence that any system developed using agent technology could not have been built just as easily using non-agent techniques Agents may make it easier to solve certain classes of problems but they do not make the impossible possible Agents are not AI by a back door Don’t equate agents and AI 10- You Get Religious Agents have been used in a wide range of applications, but they are not a universal solution For many applications, conventional software paradigms (., OO) are more appropriate Given a problem for which an agent and a non-agent approach appear equally good, prefer non-agent solution! In summary: danger of believing that agents are the right solution to every problem Other form of dogma: believing in your agent definition 10- Don’t Know Why You Want Agents Agents = new technology = lots of hype! “Agents will generate US$ billion in revenue by the year 2000” Managerial reaction: “We can get 10% of that” Managers often propose agent projects without having clear idea about what “having agents” will buy them No business plan for the project: pure research? technology vendor? solutions vendor? 10- Don’t Know Why You Want Agents Often, projects appear to be going well. (“We have agents!”) But no vision about where to go with them. The lesson: understand your reasons for attempting an agent development project, and what you expect to gain from it. 10- Don’t Know What Agents Are .