Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems Jeremy Pitt Department of Electrical and Electronic Engineering Journ´ ees Francophones sur les Syst` emes Multi-Agents (JFSMA) Plate-forme Intelligence Artificielle (PFIA) Rennes, 29/06–1/07 2015
Agenda Context: resource allocation in open multi-agent systems Problem: how to ensure that allocation is fair and sustainable Sustainability: formalisation of Elinor Ostrom ’s institutional design principles for self-governing institutions Fairness: formalisation of Nicholas Rescher ’s theory of distributive justice based on legitimate claims Computational justice in ‘technical’ and ‘socio-technical’ systems Summary and conclusions Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 2 / 22
Context Open multi-agent systems ◮ autonomous, heterogeneous, (possibly) competing components (agents) ‘Technical’ systems – composed of purely computing agents ◮ Grid computing, cloud computing, . . . ◮ Ad hoc networks, sensor networks, vehicular networks, . . . ◮ Virtual organisations, . . . ◮ Reconfigurable manufacturing, evolvable manufacturing, . . . ◮ Power systems, . . . Common requirement: a collective action situation in which the agents (aka appropriators ) have to collectivise and distribute resources, in the context of . . . Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 3 / 22
. . . Key Features of Open Systems Self-determination (no centralised ‘authority’) ◮ Selection and modification of the rules for resource allocation are determined by the agents themselves Expectation of error and corrective action ◮ Sub-ideal behaviour is to be expected (by accident, necessity or malice (free-riding)), the enforcement of sanctions for non-compliance and/or restoration of compliant states Economy of scarcity ◮ Sufficient resources to keep agents satisfied at the long-term, but insufficient to meet all demands at a particular time-point Endogeneous resources ◮ Computing a resource allocation must be ‘paid for’ from the same resources being allocated No full disclosure ◮ Agents are autonomous and their internal states cannot be checked Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 4 / 22
Methodology Introspection – ask: how do people solve this sort of problem? Aside – with the intention of applying the sociologically-inspired computing methodology Calculus 1 principled operationalisation formal characterisation Pre-formal ... Computer Theory Model Calculus n Expressive capacity Requirements coverage ⇐ ⇒ controlled theory Conceptual granularity Computational tractability experimentation construction ⇐ ⇒ Consistency Usability Observed Observed Phenomena Perfomance ◮ Communication – speech act theory ◮ Socialisation – trust, forgiveness and social networks ◮ Organisation and Deliberation – norms and rules of order Answer: evolve institutions for self-governing common-pool resource management Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 5 / 22
Common-Pool Resource Management People are very good at “making stuff up” In particular, making up and writing down conventional rules to (voluntarily) regulate/organise their own behaviour Elinor Ostrom (Nobel Laureate for Economic Science, 2009) Common-pool resource (CPR) management by self-governing institutions Avoidance (not refutation) of ‘the tragedy of the commons’, and ‘zero contribution’ thesis Alternative to privatisation or centralisation Role-based protocols for implementing conventional procedures Self-organisation : change the rules according to other (‘fixed’, ‘pre-defined’) sets of rules Self-determination : those affected by the rules participate in their selection Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 6 / 22
Self-Governing the Commons with Institutions Definition: “set of working rules that are used to determine who is eligible to make decisions in some arena, what actions are allowed or constrained, ... [and] contain prescriptions that forbid, permit or require some action or outcome” [Ostrom] Conventionally agreed, mutually understood, monitored and enforced, mutable and nested Nesting: tripartite analysis operational-, collective- and constitutional-choice rules Decision arenas [Action Situations] Requires representation of Institutionalised Power Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 7 / 22
Sustainability of the Commons Analysis: necessary conditions for successful enduring institutions ‘Supply’: handbook of institutional design principles P1 Clearly defined boundaries P2 Congruence between appropriation and provision rules and the state of the prevailing local environment P3 Collective choice arrangements P4 Monitoring by appointed agencies P5 Flexible scale of graduated sanctions P6 Access to fast, cheap conflict resolution mechanisms P7 Minimal recognition by external authorities of the right to self-organise P8 Systems of systems Apply the methodology to Ostrom’s principles Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 8 / 22
Self-Organising Electronic Institutions (SOEI) Electronic Institutions Formalise structural, functional and procedural aspects of institutions in mathematical or computational form Self-Organising: selection and modification of structures, functions, and procedures are determined by the members DG 3 DG 2 wdMethod { v ( · ) } a 2 DG 3 scr 3 scr 2 { v ( · ) } a 2 DG 2 rep 1 1 2 DG 1 DG 1 wdMethod W A DG DG A A = DG { v ( · ) } a 2 DG 1 scr 1 scr 4 { v ( · ) } a ∈ DG 1 4’ 3 a b � a b raMethod W 4 a b b ∼ a DG { d a ( · ) } a 2A ocr 2 DG DG A A A 5 inc 1 { r a ( · ) } a 2A Self-Organising electronic institutions represented in framework of dynamic norm-governed systems (Artikis, 2012) SOEI encapsulating Ostrom’s institutional design principles can be axiomatised in computational logic using the Event Calculus, and directly executed Experiments showed that the more principles that were axiomatised, it was more likely that the institution could maintain ‘high’ levels of membership and sustain the resource Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 9 / 22
“That’s Not Fair” – Distributive Justice and CPRs Is the axiomatisation of the allocation method, and the outcomes it produces, ‘ fair ’, now, (with respect to) the past, and in the future? What fairness criteria to use to distribute the resources? Egalitarian : maximise satisfaction of most disadvantaged agent Envy-free : no agent prefers the allocation of any other agent Proportional : all agents receive the same share Equitable : each agent derives the same utility . . . There are many objective metrics for measuring ‘fairness’ outcomes Limitations of existing fairness criteria: Many not appropriate under an economy of scarcity Focus on a single aspect (monistic) Often disregard temporal aspects (e.g. repeated allocations) Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 10 / 22
Experimental Setting – Linear Public Good Game (LPG) LPG commonly used to study free-riding in collective action situations Variant game: LPG ′ – in each round, each agent: Determines the resources it has available, g i ∈ [0 , 1] Determines its need for resources, q i ∈ [0 , 1] In an economy of scarcity , q i > g i Makes a demand for resources, d i ∈ [0 , 1] Makes a provision of resources, p i ∈ [0 , 1] ( p i ≤ g i ) Receives an allocation of resources, r i ∈ [0 , 1] Makes an appropriation of resources, r ′ i ∈ [0 , 1] Agents may not comply, r ′ i > r i Utility in LPG ′ : accrued resources R i = r ′ i + ( g i − p i ) � aq i + b ( R i − q i ) , if R i ≥ q i U i = aR i − c ( q i − R i ) , otherwise Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 11 / 22
Rescher’s Legitimate Claims Canons of distributive justice : treat people according to . . . . . . as equals . . . needs . . . actual productive contribution . . . efforts and sacrifices “ . . . a valuation of their socially-useful services . . . supply and demand . . . ability, merit or achievements Each canon, taken in isolation, is inadequate to achieve ‘fairness’ Distributive justice consists of evaluating and prioritising agents legitimate claims , both positive and negative Determine what the legitimate claims are, how they are accommodated in case of plurality, and how they are reconciled in case of conflict Jeremy Pitt Fair and Sustainable Resource Allocation in Self-Organising Multi-Agent Systems 12 / 22
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