The Trade-off Between Fast Learning and Dynamic Efficiency
نویسندگان
چکیده
In both static and dynamic, independent private values setups, the efficient allocation is implementable if the distribution of agents’ values is known. Lack of knowledge about the distribution is inconsequential in the static case. But, if distribution of agents’ values is not known in a dynamic framework, and if the designer gradually learns about it by observing present values, endogenously arising informational externalities may prevent the implementation of the efficient allocation if present observations have a large impact on expectations about the future. We provide necessary and sufficient conditions for the efficient allocation to be implementable, and we draw a parallel to situations with direct informational externalities.
منابع مشابه
Modeling the Trade-off between Manufacturing Cell Design and Supply Chain Design
Nowadays, we are witnessing the growth of firms that distribute the production capacity of their products to a wide geographic range to supply the demand of several markets. In this article, the relationships and interactions between cell design and supply chain design are investigated. For this purpose, a novel integrated model is presented for designing dynamic cellular manufacturing systems ...
متن کاملFuzzy Vehicle Routing Problem with Split Delivery: Trade-off between Air Pollution and Customer Satisfaction
In large-scale emergency, the vehicle routing problem focuses on finding the best routes for vehicles. The equitable distribution has a vital role in this problem to decrease the number of death and save people's lives. In addition to this, air pollution is a threat to people’s life and it can be considered to omit other kinds of disasters happens because of it. So, a new MINLP model presented ...
متن کاملDynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملTrading Expressivity for Efficiency in Statistical Relational Learning
Statistical relational learning (SRL) combines state-of-the-art statistical modeling with relational representations. It thereby promises to provide effective machine learning techniques for domains that cannot adequately be described using a propositional representation. Driven by new applications in which data is structured, interrelated, and heterogeneous, this area of machine learning has r...
متن کاملA power-efficiency trade-off in resource use alters epidemiological relationships.
Trade-offs play pivotal roles in the ecology and evolution of natural populations. However, trade-offs are probably not static, invariant relationships. Instead, ecological factors can shift, alter, or reverse the relationships underlying trade-offs and create critical genotype x environment (G x E) interactions. But which ecological factors alter trade-offs or create G x E interactions, and wh...
متن کامل