10 citations · 71 across the 49 of their papers we have counts for
8 papers · 1 filter
Deep Inductive Logic Programming meets Reinforcement Learning
Andreas Bueff, Vaishak Belle
One approach to explaining the hierarchical levels of understanding within a machine learning model is the symbolic method of inductive logic programming (ILP), which is data effic…
Statistical relational learning and neuro-symbolic AI: what does first-order logic offer?
Vaishak Belle
In this paper, our aim is to briefly survey and articulate the logical and philosophical foundations of using (first-order) logic to represent (probabilistic) knowledge in a non-te…
Toward A Logical Theory Of Fairness and Bias
Vaishak Belle
Fairness in machine learning is of considerable interest in recent years owing to the propensity of algorithms trained on historical data to amplify and perpetuate historical biase…
Learnability with PAC Semantics for Multi-agent Beliefs
Ionela G. Mocanu, Vaishak Belle, Brendan Juba
The tension between deduction and induction is perhaps the most fundamental issue in areas such as philosophy, cognition and artificial intelligence. In an influential paper, Valia…
Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures
Paulius Dilkas, Vaishak Belle
First-order model counting (FOMC) is a computational problem that asks to count the models of a sentence in finite-domain first-order logic. In this paper, we argue that the capabi…
Agency and legibility for artists through Experiential AI
Drew Hemment, Matjaz Vidmar, Daga Panas +3
Experiential AI is an emerging research field that addresses the challenge of making AI tangible and explicit, both to fuel cultural experiences for audiences, and to make AI syste…
Experiential AI: A transdisciplinary framework for legibility and agency in AI
Drew Hemment, Dave Murray-Rust, Vaishak Belle +3
Experiential AI is presented as a research agenda in which scientists and artists come together to investigate the entanglements between humans and machines, and an approach to hum…
Why not both? Complementing explanations with uncertainty, and the role of self-confidence in Human-AI collaboration
Ioannis Papantonis, Vaishak Belle
AI and ML models have already found many applications in critical domains, such as healthcare and criminal justice. However, fully automating such high-stakes applications can rais…