Spain

ECAI 2020

Entropy-based adaptive exploit-explore coefficient for Monte-Carlo path planning

monte-carlo tree search methods

entropy-based explore-exploit coefficient (ebc)

mixed-observability markov decision process (momdp)

path planning

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

technical paper

"Semantic interpretation of dynamic visuospatial imagery calls for a general and systematic integration of methods in knowledge representation and computer vision. Towards this, we highlight research articulating and developing deep (visuospatial) semantics, characterised by the existence of declarative models –e.g., pertaining space and motion– and corresponding formalisation and reasoning methods supporting capabilities such as semantic question-answering, relational visuospatial learning, and (non-monotonic) visuospatial explanation. We position a working model for deep semantics by highlighting our select recent works from IJCAI 2019, AAAI 2018, and ILP 2016 & ACS 2018. 

We posit that human-centred, explainable visual sensemaking necessitates both high-level semantics and low-level visual computing, with the highlighted works providing a model for systematic, modular integration of diverse multifaceted techniques and perspectives from AI, ML, Vision, Visual Perception, and Spatial Cognition."

Cognitive Vision and Perception: Deep Semantics Integrating AI and Vision for (Declarative) Reasoning about Space, Action, and Motion

Deep learning applied to NILM : is data augmentation worth for energy disaggregation?

ASP-based Signal Plan Configuration for Traffic Flow Optimization

Machine Learning for Gas and Oil Exploration

Point-Of-Interest Semantic Tag Completion in a Global Crowdsourced Search-and-Discovery Database

Intelligent Recommendation & Decision Technologies for Community-Driven Requirements Engineering

Cross-Border Medical Research using Multi-Layered and Distributed Knowledge

Remaining Useful Life Curve Prediction of Rolling Bearings under Defect Progression Based on Hierarchical Bayesian Regression

KnowledgeCheckeR: Intelligent Techniques for Counteracting Forgetting

FishNet: A Unified Embedding for Salmon Recognition

poster

https://d3smihljt9218e.cloudfront.net/transcript/1315/subtitle/e884bd278223bfc907bb6a46bc61f89b.vtt

English (automatic)

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Cognitive Vision and Perception: Deep Semantics Integrating AI and Vision for (Declarative) Reasoning about Space, Action, and Motion

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Next from ECAI 2020

Cognitive Vision and Perception: Deep Semantics Integrating AI and Vision for (Declarative) Reasoning about Space, Action, and Motion

Similar lecture

Monte Carlo Information-Oriented Planning

Downloads