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MAPLE Lab @ UMBC

Multi-Agent Planning and Learning Lab

Research Projects

Exploring and Visualizing Complex Models

Learning to Follow Verbal Instructions

Interactive Visual Methods for Partitioning Multidimensional Spatial Data

KEDS: Knowledge-Enhanced discovery Systems

Organizational Learning

POIROT: Plan-Order-Induction by Reasoning From One Trial

MATES: Making Agent Teams Evoke Synergy

Developing methods for dynamic organization (combinatorial strategy selection and task allocation) in multi-agent systems

Studying the effect of social graph structures on large-scale multi-agent systems

Developing constraint satisfaction methods for planning and scheduling that take into account the cost of checking constraints

Incorporating background knowledge into machine learning techniques

Interactive methods for planning, scheduling, and machine learning

VisARD: Visualizing dynamic relational models in complex domains

Virtual Telescopes in Education

Online and active learning methods for text classification

Applying AI planning techniques to perform service composition for the Semantic Web

Applying genetic algorithms to learning game playing strategies

Exploring and Visualizing Complex Models

Learning to Follow Verbal Instructions

Interactive Visual Methods for Partitioning Multidimensional Spatial Data

KEDS: Knowledge-Enhanced discovery Systems

Organizational Learning

POIROT: Plan-Order-Induction by Reasoning From One Trial

MATES: Making Agent Teams Evoke Synergy

Developing methods for dynamic organization (combinatorial strategy selection and task allocation) in multi-agent systems

Studying the effect of social graph structures on large-scale multi-agent systems

Developing constraint satisfaction methods for planning and scheduling that take into account the cost of checking constraints

Incorporating background knowledge into machine learning techniques

Interactive methods for planning, scheduling, and machine learning

VisARD: Visualizing dynamic relational models in complex domains

Virtual Telescopes in Education

Online and active learning methods for text classification

Applying AI planning techniques to perform service composition for the Semantic Web

Applying genetic algorithms to learning game playing strategies