Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System
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Summary
The design, construction and empirical evaluation of NJFun, an experimental spoken dialogue system that provides users with access to information about fun things to do in New Jersey, are reported on.
- Type
- article
- Published
- 2011-06-03
- Cited by
- 429
- References
- 37
- Access
- Open access
- OpenAlex
- https://openalex.org/W1681299129
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2198541
Keywords
Reinforcement learning, Computer science, Reinforcement, Human–computer interaction, Artificial intelligence
References
- Intelligent dialogues in automated telephone services
- Computational Models of Mixed-Initiative Interaction
- Introduction to Reinforcement Learning
- CHRONUS, The next generation
- From novice to expert: the effect of tutorials on user expertise with spoken dialogue systems
- Voice communication between humans and machines
- Metrics for Evaluating Dialogue Strategies in a Spoken Language System
- A dialog control strategy based on the reliability of speech recognition
- Evaluating spoken dialogue agents with PARADISE: Two case studies
- An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email
- An evaluation of strategies for selectively verifying utterance meanings in spoken natural language dialog
- SPoT: A Trainable Sentence Planner
- Reinforcement Learning: A Survey
- Improving Elevator Performance Using Reinforcement Learning
- Evaluation of the Dutch train timetable information system developed in the ARISE project
- Temporal Difference Learning and TD-Gammon
- A stochastic model of human-machine interaction for learning dialog strategies
- Automatic Detection of Poor Speech Recognition at the Dialogue Level
- Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for Email
- Tracking Initiative in Collaborative Dialogue Interactions
Cited by
- Have we met? MDP based speaker ID for robot dialogue
- Prompt selection with reinforcement learning in an AT&t call routing application
- Automatic instant messaging dialogue using statistical models and dialogue acts
- A framework for dialogue data collection with a simulated ASR channel
- Combining Self-motivation with Logical Planning and Inference in a Reward-seeking Agent
- Learning dialogue policies using state aggregation in reinforcement learning
- Hybridisation of expertise and reinforcement learning in dialogue systems
- Optimising a handcrafted dialogue system design
- Statistical methods for spoken dialogue management
- User simulation for spoken dialogue systems: learning and evaluation
- Hierarchical parallel markov models for interactive social agents
- Using Dialogue Acts in dialogue strategy learning : optimising repair strategies
- Adaptive natural language generation in dialogue using reinforcement learning
- Using Wizard-of-Oz simulations to bootstrap Reinforcement - Learning based dialog management systems
- A Policy-switching learning approach for adaptive spoken dialogue agents
- Effective decision-theoretic assistance through relational hierarchical models
- Learning multi-goal dialogue strategies using reinforcement learning with reduced state-action spaces
- Error Handling in the RavenClaw Dialog Management Architecture
- The Markov Assumption in Spoken Dialogue Management
- Reinforcement learning of dialogue strategies using the user's last dialogue act
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