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Deep learning is well known as a method to extract hierarchical representations of data. In this paper a novel unsupervised deep learning based methodology, named Local Binary Pattern Network (LBPNet), is proposed to efficiently extract and compare high-level over-complete features in multilayer hierarchy. The LBPNet retains the same topology of Convolutional Neural Network (CNN) — one of the most...
An agent team with differentiated skill profiles of individual members, that performs a task in a dynamic environment which exhibits significant unpredictable changes, may need to adjust its work organization in order to maintain satisfactory performance. The uncertainty of long-term effects of such modifications favors reactive, incremental, and decentralized approaches. This paper explores the idea...
The Mutual Assistance Protocol (MAP) enables members of an agent team to directly help each other whenever they jointly determine, through a bilateral distributed agreement, that such help is beneficial to the team. Its purpose is to improve the team's performance without affecting its existing organization. In this paper we define and investigate two versions of this generic protocol: the Requester-Initiated...
This paper proposes and explores an interaction protocol for incorporating helpful behavior into agent teamwork. In the proposed Mutual Assistance Protocol (MAP), an agent can directly assist a teammate who requests help, provided that the two agents jointly determine, based on their individual beliefs, that the expected outcome of the help act is in the interest of the team. This distributed decision...
This paper presents a novel approach to accessing information stored in legacy relational databases (RDB), based on Semantic Web (SW) and multiagent systems (MAS) technologies. Its purpose is to provide the users of enterprise decision-support systems with direct, flexible, and customized access to information, through high-level semantic queries, without the need to modify the underlying legacy databases...
Both everyday experience and scientific studies indicate that emotional intelligence in general, and empathy in particular, improve the effectiveness of human teamwork. Research in affective computing confirms their significance in systems where humans and artificial agents interact. This paper explores the notion of empathy between artificial agents that has so far received little attention, and...
With the maturing of research in wireless sensor networks (WSN) and the more recent advances in wireless sensor and actor networks (WSAN), there has been an increasing interest in heterogeneous self-organizing networks with multiple types of nodes that possess different capabilities and perform diverse tasks in the network's deployment, maintenance, and application functionalities. This paper explores...
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