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Leo-III is an effective automated theorem prover for extensional type theory with Henkin semantics. It is based on an extensional higher-order paramodulation calculus and supports reasoning in monomorphic and rank-1 polymorphic first-order and higher-order logics. Leo-III also automates various non-classical logics, including almost every normal higher-order modal logic.

ECAI 2020

The Higher-Order Prover Leo-III

knowledge representation and reasoning

non-classical logics

henkin semantics

automated deduction

higher-order logic

automated theorem proving

poster

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.

Actual Causality Canvas: A General Framework for Explanation-based Socio-Technical Constructs

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

"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

technical paper

https://d3smihljt9218e.cloudfront.net/transcript/1286/subtitle/32cf8dc39cd1efd114e195959bb833b6.vtt

English (automatic)

The Higher-Order Prover Leo-III

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Actual Causality Canvas: A General Framework for Explanation-based Socio-Technical Constructs

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