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Intelligent Agent Systems. Artificial Intelligence Systems that think like humans Systems that think rationally Systems that act like humans Systems that.

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Presentation on theme: "Intelligent Agent Systems. Artificial Intelligence Systems that think like humans Systems that think rationally Systems that act like humans Systems that."— Presentation transcript:

1 Intelligent Agent Systems

2 Artificial Intelligence Systems that think like humans Systems that think rationally Systems that act like humans Systems that act rationally

3 What Is Intelligence? Knows the Envrionment (B) Knows What you can do and How you can do that (D) Able to choose the best action (knows Why you choose that) (I)

4 Informatic Handles Information Store Data Centralized / Decentralized Transfer Data Internet / Computer Network Communication Protocols Analyzing & Filtering Data Software Agents

5 Turing Testing for Intelligence Natural Language Processing Knowledge Representation Automated Reasoning Machine Learning Computer Vision Robotics

6 AI Directions Directions Expert Systems Neurosciences Neural Networks Machine Learning Fuzzy Logic Intelligent Agents The Semantic Web

7 Computing Machine Languages: Assembler, Z, etc. Procedural Approach: Basic, Pascal, Cobol, Fortran, C, etc. Logical Language: Lisp Object-Oriented Programming: C++, Java Genetic Algorithm & Evolutionary Programming Agent-Oriented Computing?

8 Software Development Software Engineering meets Challenges Size Complexity Heterogeneity Control Change Semantic

9 The Foundations of Agents Micro Level Issues Macro Level Issues Technologies

10 Agent Definitions No Concensus Definition An Agent is a computional entity which - acts on behalf of a person or other entities in an automous fashion - performs its action with some level of proactivity and/or reactiveness - exhibits some level of the key attributes of learning, cooperation and mobility

11 Agent Charcteristics Intrinsic Lifespan: Transient to Long-lived Level of Cognition: Reactive to Deliberative Construction: Declarative to Procedural Mobility: Stationary to Itinerant Adaptibility: Fixed to Teachable to Autodidactic Modeling: Of environment themselves, or other agents

12 Agent Characteristics Extrinsic Locality: Local to Remote Social autonomy: Independent to Controlled Sociability: Autistic, Aware, Responsibility, Team Player Friendliness: Cooperative to Competitive to Antagonistic Interaction: Logistics, Style, Semantic Level

13 MultiAgent Systems To solve problems that are too large for a centralized single agent to do due to resource limitations. To provide solutions to inherently distributed problems. To provide solutions which draw from distributed information sources

14 Mobile Agents A mobile agent is a software entity which exits in a software environment and has ability to transport itself from one system in a network to another. A mobile agent system consists of: - An agent model - A life-cycle model - A computational model - A security model - A commutational model - A navigation model

15 Agent Applications Industry –Factory Process Control –Particle Acceleration Control –Electicity Distribution Management –Automatic Supply Chain Management Economy –Automatic Auction Systems –Business Process Management –Agent-based Computational Finance

16 Agent Applications E-Commerce –Online Trading System –Agent-based Stock market System –A Virtual market place Agents on The Internet / The Semantic Web –Information Gathering –Automatic Annotation –Global Information Management

17 Agent Applications Real-Time Control –Air Traffic Control –Urban Traffic Control –Decentralized Train Scheduling Health Care –Automatic Patient Scheduling


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