A Multi-Agent Systems Based Conceptual Ship Design Decision Support System

1. A Multi-Agent Systems Based Conceptual Ship Design Decision Support System The Ship Stability Research Centre Department of Naval Architecture and Marine Engineering Universities of Glasgow and Strathclyde Bekir S. Türkmen

2. Motivations • Design Exploration and Support • Distributed Architecture • Encapsulation of Design Experience

3. What is an agent? An Agent : one that acts or has the power or authority to act or represent another. An Intelligent Agent is the agent does the things rationally in a given situation (Russell 1995)

4. Intelligent Agents • Autonomy • Collaborative Behaviour • Adaptivity • Mobility • Proactivity • Reactivity

5. Multi-Agent Systems

6. MAS- Three Important Questions • Communication • Control • Co-ordination, Collaboration, Negotiation

7. Communication • Semantics and Syntax • KQML, FIPA-ACL • KIF, FIPA-SL FIPA-ACL (INFORM :sender ( agent-identifier :name Sender@BEKIRN:1099/JADE :addresses () :receiver (set ( agent-identifier :name Receiver@BEKIRN:1099/JADE) ) :content "Hello SSRC" ) KQML/KIF (evaluate :sender A :receiver B :language KIF :ontology motors :reply-with q1 :content (val (torque m1))) (reply :sender B :receiver A :language KIF :ontology motors :in-reply-to q1 :content (= (torque m1) (scalar 12 kgf))) FIPA-SL (query‑ref   :sender (agent-idenfier :name B)       :receiver (set (agent-identifier :name A))   :content     ((iota ?x (p ?x)))   :language FIPA-SL   :reply‑with query1)

8. Control • Centralized • Federated • Autonomous

9. Co-ordination • Auctions • Contract-Net (Task Sharing) • Planning • Game Theory • Argumentation • Catalogue of Conflicts

10. ENVIRONMENT • Acquaintance Module • List of Agents • Agents’ work definition Communication Layer User Interface • Knowledge Base for Conflicts • Rule-based • Case-based Coordination Layer Acquaintance Module • Optimisation Module • Local-Search Algorithms • Global-Search Algorithms Conflict Resolution Module Optimisation Module Learning Module • Task Layer • Knowledge Base • Wrapped Simulation Tools Task Layer Intelligent Agent Architecture Proposed IA Architecture

11. Worker Agents Decision Theoretic Agents CFD Agent Multi-Attribute Decision Maker Agent Static Stability Agent Dynamic Stability Agent Multi-Objective Optimisation Agent Evacuation Agent Geometry Transfer User Interface Agents Resistance Agent 3D Real-Time Simulation / Virtual Reality Agent Hull Generation Agent FEA Agent ……………………….. Multi-Agent System Architecture Proposed MAS Architecture

12. Decision-Theoretic Agents Ranking and Selection Methods TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) …… Decision Theoretic Agents Multi-Attribute Decision Maker Agent Multi-Objective Optimisation Algorithms VEGA (Vector Evaluated GA) NSGA (Non-Dominated Sorting GA) NSGA2 (A Fast and Elitist NSGA) SPEA/SPEA2 ( Strength Pareto Genetic Algorithm) Multi-Objective Optimisation Agent

13. Multi-Objective Optimisation • Decision-Making Before Search • Decision-Making After Search • Decision-Making during Search

14. Comparison of MOGA Methods Figure 1 Figure 2 Figure 3 Objective Functions : f1(x) = x2 ; f2(x) = (x-2)2 Figure 1. VEGA Results Figure 2. NSGA Results Figure 3. NSGA II Results

15. Integrated Decision-Making and Search • In order to reduce the calculation cost and scalability we guide the search by introducing designer preferences into search. • Applied as A Priori and Progressive, • Final Selection from Reduced Pareto-Set

16. Proposed Approach for Introducing Bias • NSGA II + TOPSIS Algorithm • Reference Point Method Approach NADIR POINT IDEAL POINT

17. Proposed Approach for Introducing Bias Continued • Two modifications to introduce bias, • Modification of Elitist Strategy • Modification of Crowding Distance Assignment • Preference is given as, one unit of a is worth at most x units of b

18. Internal Hull Subdivision Optimisation • Objectives • Survivability –Max. • Cargo Capacity (In Car Lanes) Max. • Limiting KG – Max. • Constraints • Two Adjacent Bulkhead Distance greater than SOLAS’90 Longitudinal Damage Extent, • SOLAS’ 90 Regulations,Limiting KG Reduction for operational Life cycle

19. Internal Hull Subdivision Optimisation

20. Internal Hull Subdivision Optimisation Continued Cargo Capacity (Car Lanes)

21. Internal Hull Subdivision Optimisation Results

22. Distributed Optimisation Test Problem in A Multi-Agent Systems

23. Distributed Optimisation in A MAS Early Results

24. Conclusions and Future Development • Advantages of proposed approach • Distributed Computation (Less computation time) • Distribution of Expertise (Intelligent Agent Architecture) • Integrated Multi-Criteria Decision-Making and Decision Support Environment. • Future Research • Integration with CAD Environment • Case Study for Intelligent Agents in Multi-Agent Systems

25. Questions