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MAPLE Research Overview

MAPLE Research Overview. Marie desJardins ( mariedj@cs.umbc.edu ) September 16, 2005. MAPLE. MAPLE = Multi-Agent Planning and Learning Themes: Integrated AI : Planning, learning, and interaction with other agents (human and machine) Mixed-initiative (interactive) AI systems

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MAPLE Research Overview

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  1. MAPLE Research Overview Marie desJardins (mariedj@cs.umbc.edu) September 16, 2005

  2. MAPLE Research Overview MAPLE • MAPLE = Multi-Agent Planning and Learning • Themes: • Integrated AI: Planning, learning, and interaction with other agents (human and machine) • Mixed-initiative (interactive) AI systems • Incorporating and modeling different types of knowledge • Abstractions, qualitative models, background knowledge, preference functions, … • Organizational learning in multi-agent societies • Lifelong systems, embedded in real-world environments

  3. Ph.D. students: Blaz Bulka Eric Eaton (B.A. 2003) Matt Gaston (M.S. thesis 2002)(soon to be Ph.D. 2005!) Priyang Rathod (M.S. thesis 2004) Mike Smith Qianjun Xu (M.S. thesis 2003) Undergraduates: Ryan Carr ’05 James MacGlashan ’05 Natalie Podrazik ‘05 MAPLE Research Overview Current students

  4. MAPLE Research Overview Publications (2005) • Bhagavatula, Rheingans, and desJardins (EuroVis 2005) • Bulka, Gaston, and desJardins (AAAI-05 Workshop on Multiagent Learning) • desJardins (EISTA ’05) • desJardins, Getoor, and Rathod (ECML-05) • desJardins and Wagstaff (AAAI-05) • Eaton, desJardins, and Wagstaff (AAAI-05 Spring Symposium on Persistent Assistants) • Gaston and desJardins (AAAI-05 Workshop on Multiagent Learning) • Gaston and desJardins (AAAI-05) • Gaston and desJardins (AAMAS-05) • Gaston and desJardins (FLAIRS-05) • Shanbhag, Rheingans, and desJardins (InfoVis’05) • Smith and desJardins (AAMAS-05) • Smith and desJardins (AAMAS-05 Workshop on Trust) • Viswanathan and desJardins (AAMAS-05 Workshop on Large-Scale MAS) • Xu, desJardins, and Wagstaff (DS’05 – best student paper award!) • Xu, desJardins, and Wagstaff (FLAIRS-05)

  5. MAPLE Research Overview Multi-agent systems • Pending NSF CAREER proposal • Adaptation of network structure in multi-agent societies (Matt) • Adaptation of agent strategies in networked multi-agent societies (Matt, Blaz) • Trust modeling for efficient multi-agent interactions (Mike) • “Emergent” distributed planning (Blaz) • Stable team formation strategies and protocols (Priyang)

  6. MAPLE Research Overview Machine learning with background knowledge • NSF ITR grant (KEDS: Knowledge-Enhanced Discovery System) • Representing and learning preferences over sets (Ryan, James) • Incorporating feature abstraction hierarchies into Bayes net learning (Priyang) • Classification with instance-space misclassification costs (Natalie) • Extending constrained clustering... • ... with a Gaussian propagation model (Eric) • ... with “why” queries (Eric, (Craig)) • Interactive clustering of relational data using graph layout (James, (Julia, Nataliya))

  7. MAPLE Research Overview Active learning • DARPA Integrated Learning proposal • Actively collecting background knowledge (constraints) for spectral clustering (Qianjun) • Active knowledge acquisition for plan generation and analysis

  8. MAPLE Research Overview Other research • Bioinformatics(Blaz) • Bioinformatics toolkit for amino acid data • Clustering of genomic data and supporting knowledge • Computational sequence alignment analysis • NSF grant (with Steve Freeland, Biology) • Interactive, multiattribute graph partitioning (Ryan, Priyang) • Application domains: school/political redistricting, zoning and planning, resource positioning • NSF grant (with Penny Rheingans)

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