Self-adaptation in Collective Self-aware Computing Systems

The goals of this chapter are to identify the challenges involved in self-adaptation (including learning and knowledge sharing) of multiple self-aware systems (or system collectives). We shall discuss the techniques available for dealing with the challenges identified (e.g., algorithms for conflict resolution, collective learning, and negotiation protocols), and which are appropriate given assumptions regarding the collective system architecture. We refer to notions of knowledge, learning, and adaptation; various self-awareness levels; and reference scenarios introduced in Chap. 4.

[1]  Seuss.  The Cat in the Hat Comes Back , 1958 .

[2]  William Vickrey,et al.  Counterspeculation, Auctions, And Competitive Sealed Tenders , 1961 .

[3]  Hogg,et al.  Dynamics of computational ecosystems. , 1989, Physical review. A, General physics.

[4]  Tad Hogg,et al.  Collective behavior of predictive agents , 1990 .

[5]  Tad Hogg,et al.  CAN PREDICTIVE AGENTS PREVENT CHAOS , 1992 .

[6]  Dean P. Foster,et al.  Calibrated Learning and Correlated Equilibrium , 1997 .

[7]  S. Hart,et al.  A simple adaptive procedure leading to correlated equilibrium , 2000 .

[8]  Craig Boutilier,et al.  The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems , 1998, AAAI/IAAI.

[9]  Jeffrey O. Kephart,et al.  Pseudo-convergent Q-Learning by Competitive Pricebots , 2000, ICML.

[10]  Michael P. Wellman,et al.  Auction Protocols for Decentralized Scheduling , 2001, Games Econ. Behav..

[11]  Gunes Ercal,et al.  On No-Regret Learning, Fictitious Play, and Nash Equilibrium , 2001, ICML.

[12]  Jeffrey O. Kephart,et al.  Probabilistic pricebots , 2001, AGENTS '01.

[13]  Tuomas Sandholm,et al.  Algorithm for optimal winner determination in combinatorial auctions , 2002, Artif. Intell..

[14]  J. Kephart.  Software agents and the route to the information economy , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[15]  H. Van Dyke Parunak,et al.  A Design Taxonomy of Multi-agent Interactions , 2003, AOSE.

[16]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[17]  Jeffrey O. Kephart,et al.  Multi-agent implementation of asymmetric protocol for bilateral negotiations (extended abstract) , 2003, EC '03.

[18]  Holger Giese,et al.  Multi-Agent System Design for Safety-Critical Self-Optimizing Mechatronic Systems with UML , 2003 .

[19]  Vincent Conitzer,et al.  Self-interested automated mechanism design and implications for optimal combinatorial auctions , 2004, EC '04.

[20]  Jeffrey O. Kephart,et al.  An artificial intelligence perspective on autonomic computing policies , 2004, Proceedings. Fifth IEEE International Workshop on Policies for Distributed Systems and Networks, 2004. POLICY 2004..

[21]  Rajarshi Das,et al.  Utility functions in autonomic systems , 2004 .

[22]  Holger Giese,et al.  Symbolic invariant verification for systems with dynamic structural adaptation , 2006, ICSE.

[23]  Rajarshi Das,et al.  Coordinating Multiple Autonomic Managers to Achieve Specified Power-Performance Tradeoffs , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).

[24]  Bart De Schutter,et al.  A Comprehensive Survey of Multiagent Reinforcement Learning , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[25]  Vanish Talwar,et al.  No "power" struggles: coordinated multi-level power management for the data center , 2008, ASPLOS.

[26]  Holger Giese,et al.  Tool support for the design of self-optimizing mechatronic multi-agent systems , 2008, International Journal on Software Tools for Technology Transfer.

[27]  RanganathanParthasarathy,et al.  No "power" struggles , 2008 .

[28]  Xin Yao,et al.  Resource allocation in decentralised computational systems: an evolutionary market-based approach , 2009, Autonomous Agents and Multi-Agent Systems.

[29]  Paul W. Goldberg,et al.  The Complexity of Computing a Nash Equilibrium , 2009, SIAM J. Comput..

[30]  Tarek F. Abdelzaher,et al.  AdaptGuard: guarding adaptive systems from instability , 2009, ICAC '09.

[31]  Mirko Viroli,et al.  Description and composition of bio-inspired design patterns: a complete overview , 2012, Natural Computing.

[32]  Sylvain Frey,et al.  Scenarios for an Autonomic Micro Smart Grid , 2012, SMARTGREENS.

[33]  Jacob Beal,et al.  Fast Precise Distributed Control for Energy Demand Management , 2012, 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems.

[34]  Sylvain Frey,et al.  A Holonic Control Architecture for a Heterogeneous Multi-Objective Smart Micro-Grid , 2013, 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems.

[35]  Holger Giese,et al.  Model-Driven Development of Safe Self-optimizing Mechatronic Systems with MechatronicUML , 2013, Assurances for Self-Adaptive Systems.

[36]  Ada Diaconescu,et al.  Holonic Institutions for Multi-scale Polycentric Self-governance , 2014, COIN@AAMAS/PRICAI.

[37]  Peter R. Lewis,et al.  A Taxonomy of Heterogeneity and Dynamics in Particle Swarm Optimisation , 2014, PPSN.

[38]  Jeffrey O. Kephart,et al.  A Symbiotic Cognitive Computing Perspective on Autonomic Computing , 2015, 2015 IEEE International Conference on Autonomic Computing.

[39]  Rami Bahsoon,et al.  Architectural Aspects of Self-Aware and Self-Expressive Computing Systems: From Psychology to Engineering , 2015, Computer.

[40]  Roderich Groß,et al.  Firefly-Inspired Synchronization in Swarms of Mobile Agents , 2015, AAMAS.