Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Information Systems Frontiers
Trading Financial Derivatives on the Web—An Approach Towards Automating Negotiations on OTC Markets
Information Systems Frontiers
The Dynamics of the Electronic Market: An Evolutionary Game Approach
Information Systems Frontiers
Rationality in Information Systems Support to Decision Making
Information Systems Frontiers
A Negotiation Enabling Agent Based Infrastructure: Composition and Behavior
Information Systems Frontiers
Combining Cooperative and Non-Cooperative Automated Negotiations
Information Systems Frontiers
Decision models for information systems management
Information Systems Frontiers
Strategic decision making on group collaboration under temporary constraints
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
On optimal game-tree search using rational meta-reasoning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
A Study on Strategic Points for Decision Making Under Time Constraint
3PGCIC '10 Proceedings of the 2010 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
A computing theory for collaborative and transparent decision making under time constraint
Information Systems Frontiers
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The continued growth in Web-based services supporting time-critical decision making in such as e-auction, e-bidding, e-democracy, e-negotiation demands an effective way to manage time constraints. In this study, we discuss a theory on a decision making process under time constraints which are uncommon among two decision makers. The problem on a time constraint is to evaluate time cost or the value of the entire duration of a decision making process. We define time cost by introduction of opportunity cost to its evaluation. We then propose three sets of strategic points to minimize time cost for two decision makers under uncommon time constraints. With those strategic points, decision makers accelerate time-critical decision making by 1.5 times rather than a generally accepted heuristic point of half the entire time of a decision making process.