44 citations · 71 across the 8 of their papers we have counts for
8 papers
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…
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…
Making Human-Like Trade-offs in Constrained Environments by Learning from Demonstrations
Arie Glazier, Andrea Loreggia, Nicholas Mattei +3
Many real-life scenarios require humans to make difficult trade-offs: do we always follow all the traffic rules or do we violate the speed limit in an emergency? These scenarios fo…