1. OPERAS CC : An instance of a Formal Framework for MAS Modelling based on Population P Systems P.Kefalas Dept. of Computer Science CITY COLLEGE Thessaloniki, Greece I.Stamatopoulou South-East European Research Centre, Thessaloniki, Greece M.Gheorghe Dept. of Computer Science, University of Sheffield, Sheffield, UK

2. Presentation Outline Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe The challenge: Modelling Multi-Agent Systems with Dynamic Structure OPERAS: Formal Modelling of MAS OPERAS: An Open Framework OPERAS CC : An instance of OPERAS with Population P Systems Case study: NASA Autonomous Nano- Technology Swarm Conclusions Further work

3. The challenges of modelling MAS Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Model agent’s behaviour and control Model agent communication Model change in MAS structure: Agents change Number of agents changes Communication between agents change

4. OPERAS: Formal Modelling of MAS Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe A Multi-Agent System can be defined by the tuple (O, P, E, R, A, S) containing: a set of reconfiguration rules, O, that define how the system structure evolves by applying appropriate reconfiguration operators; a set of percepts, P for the agents; the environment's model / initial configuration, E; a relation, R, defining the communication channels; a set of participating agents, A, and a set of definitions of types of agents, S, that may be present in the system.

5. OPERAS explained Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe the rules in O state the condition under which creation/removal of a communication channel between agents or introduction/removal of an agent into/from the system is possible; P is the distributed union of the sets of percepts of all participating agents; R: A  A with (A i, A j )  R, A i, A j  A meaning that agent A i may send messages to agent A j ;

6. OPERAS explained Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe A = {A 1, …, A n } where A i is a particular agent defined in terms of its individual behaviour and its local mechanism for controlling reconfiguration; S k = (Behaviour k, Control k )  S, k  Types where Types is the set of identifiers of the types of agents, Behaviour k is the part of the agent that deals with its individual behaviour and Control k is the local mechanism for controlling reconfiguration; each participating agent A i of type k in A is a particular instance of a type of agent: A i =(Beh k,Ctrl k ) i.

7. OPERAS as an open framework Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Two parts in an agent model: behaviour and control Open issues: 1.Which are the formal methods that can be used in order to model the behaviour? 2.Which are the formal methods that can to use in order to model the control? 3.Could the methods in (1) and (2) be different? 4.Should the agents' behaviour models communicate directly with other agents' behaviour models?

8. … Open issues Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe 5.Should the agents' control models communicate with other agents' control models? 6.Could communication be established implicitly through percepts of the environment? 7.Which method chosen from (1) or from (2) drives the computation of the resulting system?

9. OPERAS CC Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe We have experimented with OPERAS XC : Communicating X-machines for behaviour PPS cell inspired control In this work, we choose Population P Systems with active cells for modelling both control and behaviour.

10. OPERAS CC Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Transformation rules: to model behaviour Communication rules: to model communication Differentiation rules: to model change of type of participating agents Division rules: to model introduction of new agents to the system Death rules: to model removal of agents from the system

11. The OPERAS CC approach (informal) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Each agent is virtually divided in two regions, inner (for behaviour) and outer (for control). The agent’s behaviour is modelled as a cell with its own objects and (behavioural) rules The agent’s control is wrapped around the behaviour cell and it is a cell itself with its own objects and (control) rules

12. The OPERAS CC approach (diagrammatical) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe

13. The OPERAS CC approach (formal) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe A MAS in OPERAS CC is defined as the tuple (O, P, E, R, (A 1, … A n ), S) where: A i = (w beh, w ctrl, t), where: w beh the objects of the agent behaviour cell, w ctrl the objects of the control cell (these objects possibly hold information about the w beh objects (computation states) of neighbouring agent cells) and t  k the type of the cell;

14. The OPERAS CC approach (formal) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe O = O B  O C The rules in O B (to be applied only by the behaviour cells on the w beh objects) are the transformation rules, as well as the communications rules that move objects (messages) between cells. The rules in O C (to be applied only by the control cells on the w ctrl objects) are the birth, death, differentiation and bond-making rules of a PPS as well as environment communication rules so that there is indirect communication between the control cells.

15. The OPERAS CC approach (formal) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe P = P B  P C, the set of percepts of all participating agents where P B is the set of inputs perceived by the behaviour cells and P C is the set of inputs perceived by the control cells. E is the set of objects assigned to the environment holding information about the computation states of all the participating agents; R is the finite undirected graph that defines the communication links between the behaviour cells; S is the set of possible types of cells.

16. Computation (synchronous) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe In all the cells modelling the behaviour of the agent, all applicable rules in O B are applied; All control cells expel in the environment objects related to computation states of agents; All control cells import the computation states of neighbouring agents; All applicable rules in O C (bond-making, birth, death, differentiation) are triggered in the control cells, reconfiguring the structure of the system.

17. Autonomous Spacecrafts for Asteroid Exploration Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe NASA Autonomous Nano-Technology Swarm (ANTS) aims at the development of a mission for the exploration of space asteroids with the use of different kinds of unmanned spacecrafts: Leaders Workers, and Messengers

18. Autonomous Spacecrafts for Asteroid Exploration Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe

19. The OPERAS CC approach to the ANTS mission Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe

20. Our problem: How to express behaviour? Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Transformation rules seemed (at first) too simple to be able express behaviour (us being used to state- based approaches)… BUT … Assuming that an agent behaviour is driven by its: current state current knowledge (beliefs) current goals percepts from the environment messages received by other agents We thought we might partition objects to represent each of the above.

21. Our problem: How to express rules? Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Therefore, we found out that transformation rules of the following form will do the job: Rule: (stateObj knowledgeObjs messageObjs goalObjs perceptObj  stateObj’ knowledgeObjs’ messageObjs’ goalObjs’ actionOutputObj) Ai All objects above are attribute-value pairs of the form attribute:value, e.g. state:malfunctioning

22. Formal Modelling of Behaviour … 1 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe

23. Formal Modelling of Behaviour … 2 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe

24. Transformation Rules (behaviour) Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe A worker w i joins the leader's team of Workers: Reallocation of a messenger m i to another leader

25. Formal Modelling of Control … 1 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe O contains all transformation rules (behaviour) as well as the reconfiguration rules (birth, death and bond-making) regarding the generation of a new worker, the destruction of any kind of agent in the case it aborts the mission and the establishment of communication between a leader and members of its team

26. Formal Modelling of Control … 2 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Birth rules create a new worker w i under the command of a leader L i :

27. Formal Modelling of Control … 3 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Inputs from the environment, such as earthSendsMsg:m i, are perceived with the use of communication rules of the form:

28. Formal Modelling of Control … 4 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe A death rule removes agent instances that have aborted the mission from the model (t stands for any type of agent).

29. Formal Modelling of Control … 5 Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Bond-making rules ensure the creation of a communication bond between a leader agent and any messenger or worker that belongs to this leader's team.

30. The rest of OPERAS CC model Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe The set P contains all objects recognised by the Population P System. The environment E should initially contain objects representing the initial percepts for all agents. Initial configuration: R={(L 1,W 1 ),(L 1,W 2 ),(W 1,W 2 ),(M 1,L 1 ),(M 1,W 1 ),(M 1,W 2 )} S contains the agent types is: S = {L, W, M}

31. Conclusions … Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe OPERAS can model multi-agent systems that exhibit dynamic structure, emergent and self-organisation behaviour. The contributions of OPERAS: A formal framework for MAS modelling. The behaviour and the control of an agent are separate components which imply distinct modelling mental activities. Flexibility on the choice of formal methods to utilise and option to combine different formal methods.

32. … Conclusions Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe OPERAS CC is an instance of the general framework: PPS can be viewed as a special case for OPERAS. The distinction of modelling behaviour and control as separate, offers the ability to deal with transform- ation/communication rules separately from cell birth/division/death and bond making, with implications both at theoretical as well as practical level. Practically, during the modelling phase, one can find advantages and drawbacks at any of the behaviour or control component and switch to another formal method for this component if this is desirable.

33. Further Work Ioanna Stamatopoulou, Petros Kefalas, Marian Gheorghe Continue the investigation of how OPERAS could employ other formal methods. Working on various types of transformations that could prove its power for formal modelling. Enhance existing animation tools on Population P Systems (PPS-System). Develop more models (demonstrate applicability).

34. Thank you! P.Kefalas Dept. of Computer Science CITY COLLEGE Thessaloniki, Greece I.Stamatopoulou South-East European Research Centre, Thessaloniki, Greece M.Gheorghe Dept. of Computer Science, University of Sheffield, Sheffield, UK OPERAS CC : An instance of a Formal Framework for MAS Modelling based on Population P Systems