Multi-layered Multi-agent Situated System

1. Multi-layered Multi-agent Situated System MMASS LinguaggixCoord&Coop

2. Motivations about space • MAS models • do not explicitly consider the spatial structure of agent environment • despite of the fact that • Recent results suggest that the topology of agent interaction is critical to the nature of the emergent behavior of the MAS • A large class of problems is characterized by unavoidable spatial features: several domains deal with physical space (e.g. localization problems) or a logical space (e.g. information flow in an organizational structure) LinguaggixCoord&Coop

3. An example: mutual awareness in coordination • Coordination among people is performed through mutual perception, possibly mediated by artificial agents • Logical space (categories and their relations) provides a topology to compute mutual awareness • Mutual awareness depends on the logical distance among people LinguaggixCoord&Coop

4. MMASS A multi-layered situated MAS: agent actions and interactions are strongly dependent on their position in the structured environment • Situated in an heterogeneous environment (multi-layered) • in its properties and/or in its structure • neighborhoods are not uniform across the space • Composed by heterogeneous agents • Different capabilities and behaviors for agents of different types • Different sensitivity to external stimuli • Heterogeneous interaction mechanisms • ‘Reaction’ among adjacently situated agents • ‘Field diffusion’ throughout the spatial structure of agent environment LinguaggixCoord&Coop

5. MMASS ancestors Rooted on basic principles of • Cellular Automata • intrinsically include the notions of state and spatial structure ===> uniformity • Extension of CA-based models • GAMMA (=> Chemical abstract machine) • Chemical metaphor • Inclusion of space topology LinguaggixCoord&Coop

6. MMASS and L*MASS • Agent behavior  perception-deliberation-action mechanism • Perception of local environment (e.g. adjacent sites, fields) • Action selection according to agent state, position and type • Action execution • Language for MASS (L*MASS)  Set of primitives to specify agent actions • intra-agent : trigger() and transport() • inter-agent : emit() and react() LinguaggixCoord&Coop

7. MMASS model LinguaggixCoord&Coop

8. Multilayered Multi Agent Situated System (MMASS) • MMASS  a constellation of interacting Multi Agent Situated Systems (MASS) Construct(MASS1 … MASSn) where MASSdenotes a Multi Agent Situated System (MASS) • <Space, F, A> • Space: spatial structure of a layer of agent environment • F: set of fields propagating throughout the Space • A: set of situated agents LinguaggixCoord&Coop

9. Agent Structured Environment • Multilayered space  set of interacting spaces • Space: set P of sites arranged in a network • Each site pP is defined by <ap, Fp, Pp> where • PpP: set of sites adjacent to p • apA {}: agent situated in p • FpF: set of fields active in p LinguaggixCoord&Coop

10. Fields – at-a-distance and asynchronous interaction • Fields are • generated by agents • propagated throughout the space • perceived by other agents • <Wf, Diffusionf, Comparef, Composef> • Wf: set of field values • Diffusionf: P X Wf X P Wf X…XWf • Composef: Wf …XWf Wf • Comparef: Wf X Wf {True, False} LinguaggixCoord&Coop

11. Situated Agents 3 4 4 2 1 a • aA : <s,p,T> (s current state, p current position) • T  < T, PerceptionT, ActionT> • T: set of states that agents can assume • PerceptionT: T [N X Wf1] …[N X Wf|F|] PerceptionT(s) = (cT(s), tT(s)) • cT(s): coefficient applied to field values • tT(s): sensibility threshold to fields • An agent perceives a field fi when CompareT(ciT(s)…wfi,tiT(s)) is True • ActionT: set of allowed actions for agents of type T LinguaggixCoord&Coop

12. Language for MMASS(L*MASS) to express actions LinguaggixCoord&Coop

13. state(s): the agent state is s perceive(fi): the field fi is active in p (fiFp) and agents of type T in state s can perceive it and (Compare(ciT(s)*wfi, tiT(s)=True) The effect is the change of agent state trigger(…) action: trigger(s,fi,s’) condit: state(s), perceive(fi) effect: state(s’) LinguaggixCoord&Coop

14. position(s): the agent is situated in s empty(q), near(p,q): q is a site adjacent to p (qPp) and no agent is situated in it (q=< ,Fq,Pq>) perceive(fi): the field fi is active in p and the agent can perceive it The effect is the change of agent position transport(…) action: transport(p,fi,q) condit: position(p), empty(q), near(p,q), perceive(fi) effect: position(q), empty(p) LinguaggixCoord&Coop

15. state(s): the agent state is s present(f,p): a field f is active where the agent is situated f Fp The effect is the emission of a new field to be diffused throughout the space emit(…) action: emit(s,f,p) condit: state(s) effect: present(f, p’) for all p’  P LinguaggixCoord&Coop

16. state(s): the agent state is s agreed(ap1, ap2,…, apn): agents situated in sites {p1,p2,…,pn}Pp have previously agreed to undertake a synchronous reaction The effect is the synchronous state change of the involved agents reaction(…) action: reaction(s, ap1, ap2, …, apn,s’) condit: state(s), agreed(ap1, ap2,…, apn) effect: state(s’) LinguaggixCoord&Coop