CRP743
发表于 2025-3-26 22:52:05
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Brain-Waves
发表于 2025-3-27 04:55:16
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弯曲道理
发表于 2025-3-27 05:17:52
Evolutionary Optimization of ZIP60: A Controlled Explosion in Hyperspace,ets. The original ZIP algorithm requires the values of eight control parameters to be set correctly. A new extension of the ZIP algorithm, called ZIP60, requires the values of 60 parameters to be set correctly. ZIP60 is shown here to produce significantly better results than the original ZIP (called
convulsion
发表于 2025-3-27 10:36:37
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Introvert
发表于 2025-3-27 16:39:54
On Efficient Procedures for Multi-issue Negotiation,the issues and each of these gives a different outcome. Thus, a key problem is to decide which one to use. Given this, we study the three main alternatives: the ., the ., and the .. First, we determine equilibria for the case where each agent is uncertain about its opponent’s deadline. We then compa
cortisol
发表于 2025-3-27 20:51:09
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Geyser
发表于 2025-3-28 00:57:44
Market Efficiency, Sales Competition, and the Bullwhip Effect in the TAC SCM Tournaments,he tournament, in addition to prior measures of agent competency through customer bidding. Using these benchmarks we find statistically significant increases in intratournament market efficiency, whereas agents are generally decreasing in manufacturer market power. We find that agent market share an
cluster
发表于 2025-3-28 03:27:03
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–LOUS
发表于 2025-3-28 09:03:59
A Fast Method for Learning Non-linear Preferences Online Using Anonymous Negotiation Data,cilitate the shop agent’s search for mutually beneficial alternative bundles, we develop a method for online learning customers’ preferences, while respecting their privacy. By introducing additional parameters, we represent customers’ highly nonlinear preferences as a linear model. We develop a met
CRAB
发表于 2025-3-28 13:38:47
Adaptive Pricing for Customers with Probabilistic Valuations,e copies of a good. We show that under certain assumptions this problem can be reduced to the continuous knapsack problem (CKP). We present a new fast .-optimal algorithm for solving CKP instances with asymmetric concave reward functions. We also show that our algorithm can be extended beyond the CK