Apprentissage Multi Agent à Mémoire Bornée

National audienceNous abordons ici l'apprentissage supervisé en ligne collaboratif dans une société d'agents. La démarche adoptée est celle du maintien collectif d'une notion de consistance, ici correspondant au maintien, par révision de l'hypothèse courante, d'une hypothèse d'erreur empirique nulle. L'hypothèse prend la forme d'une formule de taille réduite et la révision repose sur les exemples mémorisés. Lors de précédents travaux, dans le cadre du projet SMILE, tous les exemples rencontrés par un agent, plus ceux transmis par d'autres agents, étaient mémorisés. Dans le travail présenté ici, chaque agent a une mémoire bornée, limitant ainsi le nombre d'exemples maintenus dans la mémoire de chaque agent. Nous proposons une adaptation du mécanisme de révision collective de SMILE prenant en compte cette restriction. Plusieurs variantes de ce mécanisme, se différenciant en particulier selon la méthode utilisée par les agents pour gérer leur mémoire, sont explorées expérimentalement. Nous observons alors dans quelle mesure ces restrictions en mémoire peuvent être dépassées résultant parfois de manière surprenante en une erreur en test plus faible que sans ces restrictions

08361 Abstracts Collection -- Programming Multi-Agent Systems

From 31th August to 5th September, the Dagstuhl Seminar 08361 ``Programming Multi-Agent Systems\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Dynamic Interest Points: A Formalism to Identify Areas to Patrol within a Continuous Environment

The multi-agent patrolling problem consists of positioning agents to minimize the idleness, which represents the time difference between two visits of a same location by at least one agent.In the literature, these locations are defined manually by setting static nodes within a graph representation. However, in the context of patrolling a continuous environment, using static nodes cannot guarantee the coverage of the whole environment. In this article, we propose to discretize the continuous environment in order to generate dynamic waypoints called interest points (IP). We prove that these dynamic IP guarantee the coverage of the whole environment while dealing with its topography and the agent's observation range. We evaluated and compared our approach by benchmarking patrolling environment dealing with different observation ranges. Experiments show that dynamic IP locations are adaptive and more efficient to locate high idleness areas compared to static IP approach

An optimized fuzzy logic model for proactive maintenance

Fuzzy logic has been proposed in previous studies for machine diagnosis, to overcome different drawbacks of the traditional diagnostic approaches used. Among these approaches Failure Mode and Effect Critical Analysis method(FMECA) attempts to identify potential modes and treat failures before they occur based on subjective expert judgments. Although several versions of fuzzy logic are used to improve FMECA or to replace it, since it is an extremely cost-intensive approach in terms of failure modes because it evaluates each one of them separately, these propositions have not explicitly focused on the combinatorial complexity nor justified the choice of membership functions in Fuzzy logic modeling. Within this context, we develop an optimization-based approach referred to Integrated Truth Table and Fuzzy Logic Model (ITTFLM) that smartly generates fuzzy logic rules using Truth Tables. The ITTFLM was tested on fan data collected in real-time from a plant machine. In the experiment, three types of membership functions (Triangular, Trapezoidal, and Gaussian) were used. The ITTFLM can generate outputs in 5ms, the results demonstrate that this model based on the Trapezoidal membership functions identifies the failure states with high accuracy, and its capability of dealing with large numbers of rules and thus meets the real-time constraints that usually impact user experience.Comment: 16 pages in single column format, 11 figures, 12th International Conference on Artificial Intelligence, Soft Computing and Applications (AIAA 2022) December 22 ~ 24, 2022, Sydney, Australi

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

miditok: A Python package for MIDI file tokenization

Recent progress in natural language processing has been adapted to the symbolic music modality. Language models, such as Transformers, have been used with symbolic music for a variety of tasks among which music generation, modeling or transcription, with state-of-the-art performances. These models are beginning to be used in production products. To encode and decode music for the backbone model, they need to rely on tokenizers, whose role is to serialize music into sequences of distinct elements called tokens. MidiTok is an open-source library allowing to tokenize symbolic music with great flexibility and extended features. It features the most popular music tokenizations, under a unified API. It is made to be easily used and extensible for everyone.Comment: Updated and comprehensive report. Original ISMIR 2021 document at https://archives.ismir.net/ismir2021/latebreaking/000005.pd

Agent programming in the cognitive era

It is claimed that, in the nascent ‘Cognitive Era’, intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we explore the contributions that agent-oriented programming can make to the development of future intelligent systems. We briefly review the state of the art in agent programming, focussing particularly on BDI-based agent programming languages, and discuss previous work on integrating AI techniques (including machine learning) in agent-oriented programming. We argue that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems. We identify a range of possible approaches to integrating AI into a BDI agent architecture. Some of these approaches, e.g., ‘AI as a service’, exploit immediate synergies between rapidly maturing AI techniques and agent programming, while others, e.g., ‘AI embedded into agents’ raise more fundamental research questions, and we sketch a programme of research directed towards identifying the most appropriate ways of integrating AI capabilities into agent programs

Exploiting Prolog for Projecting Agent Interaction Protocols

Abstract. Constrained global types are a powerful means to represent agent interaction protocols. In our recent research we demonstrated that they can be used to represent complex protocols in a very compact way, and we exploited them to dynamically verify correct implementation of a protocol in a real MAS framework, Jason. The main drawback of our previous approach is the full centralization of the monitoring activity which is delegated to a unique monitor agent. This approach works well for MASs with few agents, but could become unsuitable in communicationintensive and highly-distributed MASs where hundreds of agents should be monitored. In this paper we define an algorithm for projecting a constrained global type onto a set of agents Ags, by restricting it to the interactions involving agents in Ags, so that the outcome of the algorithm is another constrained global type that can be safely used for verifying the compliance of the sub-system Ags to the protocol specified by the original constrained global type. The projection mechanism is implemented in SWI Prolog and is the first step towards distributing the monitoring activity, making it safer and more efficient: the compliance of a MAS to a protocol could be dynamically verified by suitably partitioning the agents of the MAS into small sets of agents, and by assigning to each partition Ags a local monitor agent which checks all interactions involving Ags against the projected constrained global type. We leave for further investigation the problem of finding suitable partitions of agents in a MAS, to guarantee that verification through projected types and distributed agents is equivalent to verification performed by a single centralized monitor with a unique global type

Hedonic Seat Arrangement Problems

In this paper, we study a variant of hedonic games, called \textsc{Seat Arrangement}. The model is defined by a bijection from agents with preferences to vertices in a graph. The utility of an agent depends on the neighbors assigned in the graph. More precisely, it is the sum over all neighbors of the preferences that the agent has towards the agent assigned to the neighbor. We first consider the price of stability and fairness for different classes of preferences. In particular, we show that there is an instance such that the price of fairness ({\sf PoF}) is unbounded in general. Moreover, we show an upper bound $\tilde{d}(G)$ and an almost tight lower bound $\tilde{d}(G)-1/4$ of {\sf PoF}, where $\tilde{d}(G)$ is the average degree of an input graph. Then we investigate the computational complexity of problems to find certain ``good'' seat arrangements, say \textsc{Maximum Welfare Arrangement}, \textsc{Maximin Utility Arrangement}, \textsc{Stable Arrangement}, and \textsc{Envy-free Arrangement}. We give dichotomies of computational complexity of four \textsc{Seat Arrangement} problems from the perspective of the maximum order of connected components in an input graph. For the parameterized complexity, \textsc{Maximum Welfare Arrangement} can be solved in time $n^{O(\gamma)}$, while it cannot be solved in time $f(\gamma)^{o(\gamma)}$ under ETH, where $\gamma$ is the vertex cover number of an input graph. Moreover, we show that \textsc{Maximin Utility Arrangement} and \textsc{Envy-free Arrangement} are weakly NP-hard even on graphs of bounded vertex cover number. Finally, we prove that determining whether a stable arrangement can be obtained from a given arrangement by $k$ swaps is W[1]-hard when parameterized by $k+\gamma$, whereas it can be solved in time $n^{O(k)}$