By Munindar P. Singh (auth.), Carlos Iván Chesñevar, Eva Onaindia, Sascha Ossowski, George Vouros (eds.)
This quantity constitutes the refereed court cases of the second one foreign convention on contract applied sciences, AT 2013, held in Beijing, China, in August 2013. The 15 revised complete papers provided including invited talks have been rigorously reviewed and chosen from a number of submissions and concentrate on themes comparable to semantic applied sciences, normative multiagent platforms, digital firms and digital associations, argumentation and negotiation, belief and acceptance, purposes of contract applied sciences, contract applied sciences architectures, environments and methodologies, in addition to interdisciplinary foundations of contract technologies.
Read or Download Agreement Technologies: Second International Conference, AT 2013, Beijing, China, August 1-2, 2013. Proceedings PDF
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Extra info for Agreement Technologies: Second International Conference, AT 2013, Beijing, China, August 1-2, 2013. Proceedings
The actions that represent an agent’s request have a positive valuation as it increses its comfort level, while negative values express the cost of rescheduling. Analogous, for producer agents, the valuation function wai denotes generation costs. Now, this models in effect a coalition game, where agents can trade and reallocate energy over time schedule T . Then, a coalition is a subset of agents S ⊆ A that agree on a set of actions αS . The local worth for agent a of partaking in coalition S is given by the valuation of the actions demanded by a and executed in S, substracting the cost of actions provided for members of S: lwa (S) = 1≤i≤m ⎛ ⎞ ⎝ wa (αj )⎠ (2) αj ∈αS The overall coalition value can then be computed by summing the local worth of all coalition members: lwa (S) ν(S) = (3) a∈S 1 Complex actions can be constructed using the conjunction, disjunction and negation operators.
Finally, Section 7 provides an empirical evaluation of our eCOOP scheme. Section 8 concludes. e. consumer loads, distributed generators) represent different owners with particular, possibly conflicting user goals and behaviors, deploying an agent-based distributed control over the system holds as the natural approach for our scenario [17,14]. In this work we aim to apply the multi-agent paradigm to devise a mechanism that enables local adaptability to dynamic situations at runtime and allows coordination, as opposed to the more complex task of centralised management .
To achieve this behaviour, COSA relies on a simple negotiation protocol and two functions modelling graded relationships: adherence and leadership. The numerical degrees of these relationships determine the asynchronous dialogue in which nodes engage when negotiating, and at the same time the result of negotiations modify the numerical degrees of these relationships. The basic idea of the algorithm is simple. When a node samples the environment, it sends the observed value to its neighbouring nodes.
Agreement Technologies: Second International Conference, AT 2013, Beijing, China, August 1-2, 2013. Proceedings by Munindar P. Singh (auth.), Carlos Iván Chesñevar, Eva Onaindia, Sascha Ossowski, George Vouros (eds.)