What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of investigation include Artificial intelligence, Case-based reasoning, Plan, Hierarchical task network and Flow shop scheduling.
In the field of Artificial intelligence, his study on Game design overlaps with subjects such as Non-cooperative game.
Héctor Muñoz-Avila combines subjects such as Qualitative reasoning, Applied research, Knowledge management, Reasoning system and Data science with his study of Case-based reasoning.
His Plan study combines topics in areas such as Generative grammar and Operations research.
He has included themes like Machine learning, Soundness and Knowledge engineering in his Hierarchical task network study.
His Flow shop scheduling research overlaps with Order and Planner.
His most cited work include:
- SHOP: Simple Hierarchical Ordered Planner (370 citations)
- Conversational Case-Based Reasoning (178 citations)
- Total-order planning with partially ordered subtasks (120 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Plan, Case-based reasoning, Domain and Hierarchical task network.
His work in Artificial intelligence covers topics such as Machine learning which are related to areas like Domain knowledge.
His Plan research is multidisciplinary, relying on both Human–computer interaction and Adaptation.
His research investigates the connection between Case-based reasoning and topics such as Operations research that intersect with problems in Planning algorithms.
He has researched Domain in several fields, including Set, Business system planning and Nondeterministic algorithm.
His research investigates the link between Hierarchical task network and topics such as Software engineering that cross with problems in Project plan.
He most often published in these fields:
- Artificial intelligence (56.12%)
- Plan (30.22%)
- Case-based reasoning (23.74%)
What were the highlights of his more recent work (between 2012-2021)?
- Artificial intelligence (56.12%)
- Autonomy (7.19%)
- Goal reasoning (4.32%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Autonomy, Goal reasoning, Multimedia and Hierarchical task network.
The concepts of his Artificial intelligence study are interwoven with issues in Domain, Machine learning and Action.
His biological study deals with issues like Case-based reasoning, which deal with fields such as State.
The various areas that Héctor Muñoz-Avila examines in his Goal reasoning study include Robotics, Management science, Knowledge management and Natural language processing.
His Hierarchical task network study frequently draws connections to other fields, such as Set.
His Plan research includes themes of Ontology, Information retrieval, Key and Abstraction.
Between 2012 and 2021, his most popular works were:
- Multimodal Entity Coreference for Cervical Dysplasia Diagnosis (39 citations)
- Learning hierarchical task network domains from partially observed plan traces (32 citations)
- MIDCA: a metacognitive, integrated dual-cycle architecture for self-regulated autonomy (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
Héctor Muñoz-Avila focuses on Artificial intelligence, Hierarchical task network, Autonomy, Action and Course of action.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Management science and Knowledge management.
His Hierarchical task network research is multidisciplinary, incorporating perspectives in Domain, Machine learning and Set.
Héctor Muñoz-Avila has researched Domain in several fields, including Solver and Hierarchical control system.
His research integrates issues of Consistency, Representation and Domain knowledge in his study of Machine learning.
He integrates many fields, such as Course of action and engineering, in his works.
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