Multi-Party Negotiation When Agents Have Subjective Estimates of Bargaining Powers

This paper presents a method for generating Pareto-optimal solutions in multi-party negotiations. In this iterative method, decision makers (DMs) formulate proposals that yield a minimum payoff to their opponents. Each proposal belongs to the efficient frontier, DMs try to adjust to a common one. In this setting, each DM is supposed to have a given bargaining power. More precisely each DM is supposed to have a subjective estimate of the power of the different parties. We study the convergence of the method, and provide examples where there is no possible agreement resulting from it.

Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

First report of a novel plant lysozyme with both antifungal and antibacterial activities.

A novel lysozyme exhibiting antifungal activity and with a molecular mass of 14.4 kDa in SDS–polyacrylamide gel electrophoresis was isolated from mung bean (Phaseolus mungo) seeds using a procedure that involved aqueous extraction, ammonium sulfate precipitation, ion exchange chromatography on CM-Sephadex, and high-performance liquid chromatography on POROS HS-20. Its N-terminal sequence was very different from that of hen egg white lysozyme. Its pI was estimated to be above 9.7. The specific activity of the lysozyme was 355 U/mg at pH 5.5 and 30 °C. The lysozyme exhibited a pH optimum at pH 5.5 and a temperature optimum at 55 °C. It is reported herein, for the first time, that a novel plant lysozyme exerted an antifungal action toward Fusarium oxysporum, Fusarium solani, Pythium aphanidermatum, Sclerotium rolfsii, and Botrytis cinerea, in addition to an antibacterial action against Staphylococcus aureus.