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Found 15 papers, 0 papers with code
Meta-operators for Enabling Parallel Planning Using Deep Reinforcement Learning
There is a growing interest in the application of Reinforcement Learning (RL) techniques to AI planning with the aim to come up with general policies.
Multimodal Classification of Teaching Activities from University Lecture Recordings
The way of understanding online higher education has greatly changed due to the worldwide pandemic situation.
Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes
The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application.
Spillover Algorithm: A Decentralized Coordination Approach for Multi-Robot Production Planning in Open Shared Factories
Open and shared manufacturing factories typically dispose of a limited number of robots that should be properly allocated to tasks in time and space for an effective and efficient system performance.
A context-aware knowledge acquisition for planning applications using ontologies
Automated planning technology has developed significantly.
Extending planning knowledge using ontologies for goal opportunities
Approaches to goal-directed behaviour including online planning and opportunistic planning tackle a change in the environment by generating alternative goals to avoid failures or seize opportunities.
Learning STRIPS Action Models with Classical Planning
This paper presents a novel approach for learning STRIPS action models from examples that compiles this inductive learning task into a classical planning task.
Cooperative Multi-Agent Planning: A Survey
Cooperative multi-agent planning (MAP) is a relatively recent research field that combines technologies, algorithms and techniques developed by the Artificial Intelligence Planning and Multi-Agent Systems communities.
Handling PDDL3.0 State Trajectory Constraints with Temporal Landmarks
Temporal landmarks have been proved to be a helpful mechanism to deal with temporal planning problems, specifically to improve planners performance and handle problems with deadline constraints.
Evaluating the quality of tourist agendas customized to different travel styles
In this paper, we deal with the task of creating a customized tourist agenda as a planning and scheduling application capable of conveniently scheduling the most appropriate goals (visits) so as to maximize the user satisfaction with the tourist route.
Sentiment Analysis in Social Networks through Topic modeling
In this paper, we analyze the sentiments derived from the conversations that occur in social networks.
Game-theoretic Approach for Non-Cooperative Planning
When two or more self-interested agents put their plans to execution in the same environment, conflicts may arise as a consequence, for instance, of a common utilization of resources.
A Flexible Coupling Approach to Multi-Agent Planning under Incomplete Information
Multi-agent planning (MAP) approaches are typically oriented at solving loosely-coupled problems, being ineffective to deal with more complex, strongly-related problems.
An approach to multi-agent planning with incomplete information
Multi-agent planning (MAP) approaches have been typically conceived for independent or loosely-coupled problems to enhance the benefits of distributed planning between autonomous agents as solving this type of problems require less coordination between the agents' sub-plans.
FMAP: Distributed Cooperative Multi-Agent Planning
Although FMAP is specifically aimed at solving problems that require cooperation among agents, the flexibility of the domain-independent planning model allows FMAP to tackle multi-agent planning tasks of any type.
