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» Recommendation as a Stochastic Sequential Decision Problem
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AAAI
2007
13 years 7 months ago
An Ironing-Based Approach to Adaptive Online Mechanism Design in Single-Valued Domains
Online mechanism design considers the problem of sequential decision making in a multi-agent system with self-interested agents. The agent population is dynamic and each agent has...
David C. Parkes, Quang Duong
AAAI
2004
13 years 6 months ago
Stochastic Local Search for POMDP Controllers
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
Darius Braziunas, Craig Boutilier
ACMICEC
2007
ACM
154views ECommerce» more  ACMICEC 2007»
13 years 8 months ago
Learning and adaptivity in interactive recommender systems
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
Tariq Mahmood, Francesco Ricci
AAAI
2000
13 years 6 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
NIPS
2004
13 years 6 months ago
Approximately Efficient Online Mechanism Design
Online mechanism design (OMD) addresses the problem of sequential decision making in a stochastic environment with multiple self-interested agents. The goal in OMD is to make valu...
David C. Parkes, Satinder P. Singh, Dimah Yanovsky