RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents.
Tomoyuki KagayaThong Jing YuanYuxuan LouJayashree KarlekarSugiri PranataAkira KinoseKoki OguriFelix WickYang YouPublished in: CoRR (2024)
Keyphrases
- reactive agents
- multi agent systems
- multi agent
- single agent
- action selection
- multi agent planning
- multiagent systems
- decision theoretic
- information retrieval
- image database
- multiple agents
- incomplete knowledge
- information retrieval systems
- uncertain environments
- intelligent agents
- cooperative
- software agents
- autonomous agents
- document retrieval
- image retrieval
- contextual information
- query expansion
- dynamic environments
- relevance feedback
- information gathering
- decision making
- mobile agents
- plan execution
- planning process
- artificial agents
- agent architecture
- real time strategy games
- intelligent behavior
- partial plans
- multi modal
- incomplete information
- main memory
- agent systems
- retrieval systems
- test collection
- agent behavior
- real time search algorithms
- past experience
- multi party
- game theoretic
- agent model
- coalition formation
- agent technology
- resource allocation
- language model
- case based reasoning
- multimedia
- search engine