Robust Regulation Adaptation in Multi-Agent Systems

Abstract

Adaptive organisation-centred multi-agent systems can dynamically modify their organisational components to better accomplish their goals. Our research line proposes an abstract distributed architecture (2-LAMA) to endow an organisation with adaptation capabilities. This article focuses on regulation-adaptation based on a machine learning approach, in which adaptation is learned by applying a tailored case-based reasoning method. We evaluate the robustness of the system when it is populated by non compliant agents. The evaluation is performed in a peer-to-peer sharing network scenario. Results show that our proposal significantly improves system performance and can cope with regulation violators without incorporating any specific regulation-compliance enforcement mechanisms.

Norm emergence in multiagent systems: a viewpoint paper

“…Norm synthesis can be done both offline and online. Online synthesis is useful for determining the set of norms that avoid conflicting states while the system is running [4,26,68,[70][71][72]. Offline synthesis, though useful, is difficult to do when all possible states of the system are not known during design time or can change based on interactions of actors within the system.…”

“…This deontic logic perspective on norms is widely studied in the literature. Research here includes but is not limited to: (i) frameworks to describe and model norms as deontic logic in institutions 3 for example: InstAL [31], JaCaMo [22], OperettA [2]; (ii) the development of agents that reason about norms in their decision making for example: BDI (Belief-Desire-Intention) and BOID (Belief-Obligation-Intention-Desire) [19,24,35,38], Normative KGP (Knowledge-Goals-Plans) agents [84], NBDI(Norm-Belief-Desire-Intention) [41] (iii) approaches to synthesising normative systems for example: IRON and SENSE [70,71,73], AOCMAS [26], Guard functions in [4]. (iv) and more recently values and norms, for example [18,34,94].…”

“…Norm emergence or convergence is widely accepted to have happened, or a norm is said to have emerged, when a predetermined percentage of the population observes the Balaraman and Singh [13] Beheshti and Sukthankar [16] Beheshti et al [17] Bench-Capon and Modgil [18] Boissier et al [22] Boella and van der Torre [20] Boella and van der Torre [19] Boyd and Richerson [23] Broersen et al [24] Brooks et al [25] Campos et al [26] Chakrabarti and Basu [28] Chao Yu et al [29] Cliffe et al [31] Conte and Castelfranchi [32] Criado et al [35] Dascalu et al [37] Dastani and van der Torre [38] dos Santos Neto et al [41] Franks et al [42] Frantz et al [43] Ghorbani et al [48] Ghorbani and Bravo [46] Hoffmann [55] Hofmann et al [56] Hassani-Mahmooei and Parris [53] Hao and Leung [49] Hao et al [50] Hao et al [51] Hao et al [52] Hu and Leung [57] Hübner et al [58] Lopez [65] Lotzmann et al [66] Lee et al [61] Mahmoud et al [67] Mashayekhi et al [68] Mukherjee et al [75] Mungovan et al [76] Morales et al [70] Morales et al [72] Morales et al [71] Mor...…”

“…There are a few exceptions however, for example Morales et al [70][71][72], Alechina et al [4], Mashayekhi et al [68] and Campos et al [26] that investigate mechanisms for the online synthesis of norms. This in contrast to Li [62], who advances a synthesis mechanism for offline use aimed at designers, although it could in principle be delivered as an online service.…”

Um modelo de mecanismo adaptativo de sanções para sistemas multiagentes normativos.

“…As in electronic institutions (Section 3.3.1), each external agent is associated with an institutional component for sanctioning, which adapts policies to promote norm compliance by agents. Similarly, Campos et al (2013) propose an adaptation mechanism that modifies norm penalties according to agents' behaviors through the use of case-based reasoning (AAMODT; PLAZA, 1994) to learn the best ways to regulate them in each situation.…”