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A robotic implementation of rules for social self-regulation EmergeNET presentation 23 rd March 2009 Torbjørn S. Dahl University of Wales, Newport.

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Presentation on theme: "A robotic implementation of rules for social self-regulation EmergeNET presentation 23 rd March 2009 Torbjørn S. Dahl University of Wales, Newport."— Presentation transcript:

1 A robotic implementation of rules for social self-regulation EmergeNET presentation 23 rd March 2009 Torbjørn S. Dahl University of Wales, Newport

2 Defying the rules: How self-regulatory social systems work Prof Kim Christensen, Imperial College Dr Ana Sendova-Franks, UWE Dr Angela Espinosa, Hull University Dr Torbjørn Dahl, University of Wales, Newport Aim: To find a set of generic rules that describe emergent self-regulation in ant, human and robotic social systems

3 Ants display specialisation A small fraction of the ants to a large fraction of a task Task Ants

4 Sufficient and necessary requirements for emergent self-regulation An example of emergent self- regulation in ant systems is division of labour Presence of at least two tasks Differentiation among agents Concurrency of tasks Flexibility in agents

5 The attractive field model (AFM) of emergent self-regulation The AMF model is a bi-partite graph Information flow from tasks

6 Task attraction i – ant, j – task r – position, δ – avoids division by zero k – learning factor Φ – Max number of ants on task Ψ – Current number ants on task Θ – temporal availability

7 Action selection Discrete time steps Random action selection based on task stimuli Sensitisation and desensitisation:

8 Initial results As individuals specialise, tracks become straighter and spatial distributions more distinct

9 AFM in (Temnothorax) ants o – ants x – tasks (brood sorting, exploring, grooming, random wandering wall construction AF – stimuli to perform a given task Simulation reproduces data from observations Ongoing studies to refine AFM, in particular w.r.t. learning

10 AFM in human social systems o – humans x – tasks AF – motivation to undertake task (understanding, interest, proximity, politics)

11 The viable systems model (VSM) Recursive model of tasks required for systems to be viable 1. Tasks 2. Coordination 3. Monitoring and regulation 4. External factor monitoring 5. Strategic vision

12 Flow of information in human social systems Pedro Pablo Cardoso from the University of Hull is currently studying an eco-village in Ireland The village aims to be self-organised Initially, a number of tasks were ignored The VSM model has been introduced to the villagers

13 Flow of information in human social systems Observing the elements of AFM Differentiation (skill levels, empowerment) Concurrency (activity of multiple S1 and S2 taks) Flexibility (changing tasks) Recording data about communication Communication channels Type and quality of information exchange Failures in communication Recording data about tasks covered From meeting minutes Uncovered tasks

14 AFM in robot societies x – robots o – (manufacturing) tasks AF – Robot task awareness

15 Evaluation of AFM in robots Task selection and learning is programmed into the robots Task data and attractive fields implemented on a separate server Three models of information flow will be compared: 1. Global broadcast of tasks 2. Local (robot-robot) communication 3. Stigmergic communication through artificial pheromones

16 Experimental infrastructure

17 Metrics for self-regulation Task completion rates Active tasks Spatial distribution

18 Future tasks Accommodating emergent task specialisation within a pre- programmed setup Pre-program tasks using an implementation of the VSM Introduce mechanisms to identify and accommodate new tasks or specialisations


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