44 citations · 83 across the 13 of their papers we have counts for
12 papers · 1 filter
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Vishal Pallagani, Kaushik Roy, Bharath Muppasani +7
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive review of 126 pap…
Proceedings 39th International Conference on Logic Programming
Enrico Pontelli, Stefania Costantini, Carmine Dodaro +7
This volume contains the Technical Communications presented at the 39th International Conference on Logic Programming (ICLP 2023), held at Imperial College London, UK from July 9 t…
Value-based Fast and Slow AI Nudging
Marianna B. Ganapini, Francesco Fabiano, Lior Horesh +7
Nudging is a behavioral strategy aimed at influencing people's thoughts and actions. Nudging techniques can be found in many situations in our daily lives, and these nudging techni…
Understanding the Capabilities of Large Language Models for Automated Planning
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan +5
Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Lan…
Fast and Slow Planning
Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini +5
The concept of Artificial Intelligence has gained a lot of attention over the last decade. In particular, AI-based tools have been employed in several scenarios and are, by now, pe…
Plansformer: Generating Symbolic Plans using Transformers
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan +5
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP). From BERT to BLOOM, LLMs have surpass…
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Marianna B. Ganapini, Murray Campbell, Francesco Fabiano +8
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that…
Thinking Fast and Slow in AI: the Role of Metacognition
Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano +7
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life. However, we are still mostly seeing instances of narrow AI: ma…
E-PDDL: A Standardized Way of Defining Epistemic Planning Problems
Francesco Fabiano, Biplav Srivastava, Jonathan Lenchner +3
Epistemic Planning (EP) refers to an automated planning setting where the agent reasons in the space of knowledge states and tries to find a plan to reach a desirable state from th…
Thinking Fast and Slow in AI
Grady Booch, Francesco Fabiano, Lior Horesh +8
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the c…
Modelling Multi-Agent Epistemic Planning in ASP
Alessandro Burigana, Francesco Fabiano, Agostino Dovier +1
Designing agents that reason and act upon the world has always been one of the main objectives of the Artificial Intelligence community. While for planning in "simple" domains the…
Design of a Solver for Multi-Agent Epistemic Planning
Francesco Fabiano
As the interest in Artificial Intelligence continues to grow it is becoming more and more important to investigate formalization and tools that allow us to exploit logic to reason…