A Unified Framework for Collective Systems

788 vues

Publié le

Emma Hart: Edinburgh Napier University
Jeremy Pitt: Imperial College London
Ulle Endriss: University of Amsterdam

Presentation from ECAL 2013

Publié dans : Technologie, Business
0 commentaire
0 j’aime
  • Soyez le premier à commenter

  • Soyez le premier à aimer ceci

Aucun téléchargement
Nombre de vues
Sur SlideShare
Issues des intégrations
Intégrations 0
Aucune incorporation

Aucune remarque pour cette diapositive

A Unified Framework for Collective Systems

  1. 1. A UNIFIED FRAMEWORK FOR COLLECTIVE SYSTEMS Emma Hart, Edinburgh Napier University Jeremy Pitt, Imperial College London Ulle Endriss, University of Amsterdam
  2. 2. Grand Vi i G d Vision Applications A Software Toolkit of Design Patterns and Components p A Unified Theory of Operations for CAST Systems y
  3. 3. Why do Wh d we need a new theory ? d h • Existing engineering approaches provide some theoretical basis • E.g. control theory – ensure/prove stability • But most methods don’t account for defining t f d fi i properties of CAST systems • Lead to systems that are oscillatory or at worst unfit for purpose • Existing methods often domain-driven (e g (e.g. telecoms, robotics) • Not generalisable or transferable
  4. 4. CAS i M l i Di i li is Multi-Disciplinary • Many theories from individual disciplines • Hard to compare theories • Theories address different aspects of CAS • Don’t account for Don t engineering constraints
  5. 5. Towards a unified theory T d ifi d h • Unifies concepts from multiple disciplines into a single framework • Qualitative theory represented in a o at c o axiomatic form • Can be formalised and analysed • Operationalised via design patterns Biological Systems Computational Social Choice Organisational Theory
  6. 6. Biological Systems Bi l i l S • Immune-neuro- • Long-term stability endocrine mechanisms lead to homeostasis • Cohen’s cognitive immune system : • Adapt over multiple • Decision making via co- respondence • Swarm insects • Coordination, partial info • Symbiosis between multiple species: • C Cooperation ti timescales ti l • Coordinate multiple heterogeneous components • Deal with limited and partial information • Decision making • Conflict resolution
  7. 7. Social Choice Theory S i l Ch i Th • Originates in economics and political science • Concerns design & analysis of methods for aggregating preferences of multiple agents into collective decisions • Social choice considers formal aspects of democratic decision making (e.g electoral systems) t ) • Computational Social g Choice add an algorithmic perspective • • • • • • Heterogeneous agents Multiple objectives Collective decisions Open-ness Fair division of resources Stability
  8. 8. Organisational Th O i i l Theory • Elucidates principles for stable resource management • Study of engineered systems • Insights into engineering sociotechnical ‘organisations’ in a top down manner • Collective Action • Trust • Cooperation • Stable and enduring g systems
  9. 9. A Unified Th U ifi d Theory of O f Operation i New CAST propertie w es… Con nflicts Engineering Requirements of CAST Systems D Diverse Objective O es Organisational Theory S Social Interaction ns Biological Systems Noisy Inf formation n Computational Social Choice Open n-ness A Unified Theory of Operations for CAST Systems
  10. 10. What d Wh does synthesis give ? h i i Biological  g Systems Computational  Social Choice Biological  Biological Systems Organisational Theory Engineering Constraints Computational  p Social Choice >> Engineering Constraints • Addresses weaknesses in individual theories • Addresses conflicts • Respects engineering constraints Organisational Theory
  11. 11. Individual Weaknesses I di id l W k • Biological Systems: • Tend to rely on homogeneous collectives • Global rather than individual objectives • Considerable physical differences • Computational Social Choice • Based on standard models from economics • Abstracted from human decision making (different goals but same model) • Institutional Theories • Easy to get locked into sub-optimal states due to path dependencies • Not clear how to evaluate ‘fitness’ of an institution fitness
  12. 12. Conclusions C l i • Unification addresses current fragmented approach to inter-disciplinary research • Diff Different analysis t l currently hi d elucidating t l i tools tl hinder l id ti connections between fields • Many existing theories don’t account for engineering don t constraints of CAS • A unified theory will: • Enable formal comparison between concepts from different disciplines • Drive innovation in field