this paper investigates the fault detection filter and consensus control of positive multi-agentsystems with disturbances and faults. First, a kind of positive fault detection filter is designed by virtue of the posi...
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Active Inference is a framework that emphasizes the interaction between agents and their environment. While the framework has seen significant advancements in the development of agents, the environmental models are of...
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ISBN:
(纸本)9783031771378;9783031771385
Active Inference is a framework that emphasizes the interaction between agents and their environment. While the framework has seen significant advancements in the development of agents, the environmental models are often borrowed from reinforcement learning problems, which may not fully capture the complexity of multi-agent interactions or allow complex, conditional communication. this paper introduces Reactive Environments, a comprehensive paradigm that facilitates complex multi-agent communication. In this paradigm, bothagents and environments are defined as entities encapsulated by boundaries with interfaces. this setup facilitates a robust framework for communication in nonequilibrium-Steady-State systems, allowing for complex interactions and information exchange. We present a Julia package ***, which is a specific implementation of Reactive Environments, where we utilize a Reactive programming style for efficient implementation. the flexibility of this paradigm is demonstrated through its application to several complex, multi-agent environments. these case studies highlight the potential of Reactive Environments in modeling sophisticated systems of interacting agents.
Advances in digitization and resource-sharing business models have created new opportunities for manufacturing companies, enhancing competitiveness and resilience. However, these benefits bring computational challenge...
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this paper investigates the bi-objective scheduling problem of a flexible robotic cell capable of processing different types of jobs. Initially, a mixed integer programming model is formulated to minimize both cycle t...
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the proceedings contain 16 papers. the topics discussed include: model checking of optimal LTL and ASAP properties;on optimizing simulation-based verification of cyber-physical systems via statistical model checking: ...
the proceedings contain 16 papers. the topics discussed include: model checking of optimal LTL and ASAP properties;on optimizing simulation-based verification of cyber-physical systems via statistical model checking: a preliminary work;recent results on computable and compositional semantics for hybrid systems;temporal many-valued conditional logics: an abridged report;towards ASP-based minimal unsatisfiable cores enumeration for LTLf;formalizing decisional and operational roles in legal contracts via term-modal logic;integrating L0 regularization into multi-layer logical perceptron for interpretable classification;and automated synthesis of certified neural networks: initial results and open research lines.
In increasingly autonomous and highly distributed multi-agentsystems, centralized coordination becomes impractical and raises the need for governance and enforcement mechanisms60;from an agent-centric perspective....
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After fact finding on the disruption bought by today’s Generative AI tools to the education system, we outline the advantages of joining the disruption, motivated by the natural synergies between today’s Generative ...
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the proceedings contain 13 papers. the topics discussed include: tailoring health: contextual variables in health recommender systems;explaining decision-making between exploration and repetition: key factors for phys...
the proceedings contain 13 papers. the topics discussed include: tailoring health: contextual variables in health recommender systems;explaining decision-making between exploration and repetition: key factors for physical activity recommendations;personalized music recommendation for people with autism spectrum disorder;recommending news articles for public health intelligence;improving the prediction of individual engagement in recommendations using cognitive models;advancing visual food attractiveness predictions for healthy food recommender systems;position paper: towards recommender system supported contact tracing for cost-efficient and risk aware infection suppression;prompting large language models for tailored exercise recommendations in office spaces;and personalizing exercise recommendations with explanations using multi-armed contextual bandit and reinforcement learning.
the Web is populated by autonomous agents that act on behalf of users to perform tasks on the Web. these agents are required to interact with online systems to achieve their goals. However, they are usually designed t...
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Today, Python is the main language for developing deep learning models and solving similar problems. this language has gained great popularity due to its minimalistic and quite expressive syntax, as well as a large nu...
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