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Complexity and Emergence in Robotics Systems Design

Complexity and Emergence in Robotics Systems Design. SERENDIPITY SYNDICATE 1 : Talk. Professor George Rzevski The Open University and Magenta Corporation. Magenta Corporation is my research vehicle. Founded in 1999 Headquarters in London 200 programmers in Samara, Russia

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Complexity and Emergence in Robotics Systems Design

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  1. Complexity and Emergence in Robotics Systems Design SERENDIPITY SYNDICATE 1 : Talk Professor George Rzevski The Open University and Magenta Corporation

  2. Magenta Corporation is my research vehicle • Founded in 1999 • Headquarters in London • 200 programmers in Samara, Russia • Develops ontology-based large-scale multi-agent systems for • Real-time management (scheduling) • Knowledge discovery • Semantic analysis and search

  3. Intelligence at Work Real World real world objects and events informal information system formal information system Intelligent Agent (a person, a team, a robot, a family of robots) Cognitive/emotional filter: knowledge, attitudes, values, mental skills, social skills

  4. Thesis 1 Intelligence is given to humans Thesis 2 Intelligence is an emergent property of complex systems What is the Origin of Intelligence?

  5. Complexity and Intelligence Large-scale complex systems, such as a human being, or aswarm of software agents, exhibit remarkable emergent capabilities: • Achieving goals under conditions of uncertainty • Interpreting meaning of words and images • Recognising patterns • Learning from experience, by discovery and through communication • Creating ideas; designing artefacts These capabilities are aspects of Intelligence

  6. Multi-Layered Complexity and Intelligence • A team of humans or a swarm of swarms of software agents (in competition and/or co-operation with each other) produce even more powerful emergent intelligence • Note that a team is a network of networks of neurons

  7. A situation is complex if: It consists of a large number of diverse components, called Agents, engaged in unpredictable interaction (Uncertainty) Its global behaviour emerges from the interaction of local behaviours of Agents (Emergence)and there are always many different ways (Variety) of achieving the same global result A small disturbance may cause large changes in its global behaviour (Self-acceleration) whilst large disturbances may be unnoticed (Butterfly Effect) It self-organisesto accommodate unpredictable external or internal Events (Adaptability and Resilience) and therefore its global behaviour is “far from equilibrium” or “at the edge of chaos” It co-evolves with its environment (Irreversibility) What is Complexity?

  8. Molecules of air subjected to a heat input; autocatalytic chemical processes; self-reproduction of cells; brain Colonies of ants; swarms of bees; ecology Cities; human communities; epidemics; terrorist networks Free market; global economy; supply chains; logistics; management teams Multi-agent systems (robot brains?) Examples of Complex Systems

  9. There exists compelling evidence that as the evolution of our Universe takes its course, the ecological, social, political, cultural and economic environments within which we live and work increase in Complexity This process is irreversible and manifests itself in a higher Diversity of emergent structures and activities and in an increased Uncertainty of outcomes Source of Complexity?

  10. Evolution of English Language Shakespeare Chaucer Constructive destructions

  11. Evolution of Society Information Society Industrial Society Agricultural Society

  12. Examples of Robotics Systems Designs In all examples that follow the intention was to design complexity into robotics systems to obtain emergent intelligence

  13. A Swarm of Agents Controlling a Robot Safety Agent Performance Agent Bookkeeping Agent Scheduling Agent Maintenance Agent

  14. Intelligent Geometry Compressor Efficiency Agent Vane 1 Agent Vane 2 Agent Vane3 Agent Vane4 Agent

  15. A Family of Space Robots robot 5 robot 2 robot 1 robot 3 robot 4

  16. A Colony of Agricultural Machinery mini-tractor 5 mini-tractor 2 mini-tractor 1 mini-tractor 3 mini-tractor 4

  17. Global Logistics Network Destination 1 Destination 2 Supplier 1 Intelligent parcels Intelligent parcels Intelligent parcels transporter store store transporter transporter store store

  18. Intelligent Behaviour of Swarms of Software Agents • If software agents are instructed exactly what to do they behave as conventional programs • If software agents have no guidance how to behave they exhibit random behaviour • Intelligent behaviour emerges only under certain conditions of uncertainty – when agents have an appropriate amount of freedom to experiment.

  19. Levels of emergent intelligence are affected by the Intellectual Bandwidth of Agents (humans, robots) Agents can exchange Data (narrow bandwidth) Knowledge (wide bandwidth) Wisdom (exceedingly wide bandwidth) Intellectual Bandwidth and Teamwork

  20. Conclusions • Intelligence is an emergent property of complex systems • Artificial complex systems exhibit intelligent behaviour under certain conditions: • An appropriate degree of uncertainty (freedom to Agents) • Wide Intellectual Bandwidth (exchange of knowledge)

  21. “Build complexity into an artefact to make it adaptable……. to have artefacts of all kind capable of adapting and being resilient…” Professor George Rzevski

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