23 citations · 97 across the 30 of their papers we have counts for
13 papers · 1 filter
Active Altruism Learning and Information Sufficiency for Autonomous Driving
Jack Geary, Henry Gouk, Subramanian Ramamoorthy
Safe interaction between vehicles requires the ability to choose actions that reveal the preferences of the other vehicles. Since exploratory actions often do not directly contribu…
Building Affordance Relations for Robotic Agents - A Review
Paola Ardón, Èric Pairet, Katrin S. Lohan +2
Affordances describe the possibilities for an agent to perform actions with an object. While the significance of the affordance concept has been previously studied from varied pers…
From Demonstrations to Task-Space Specifications: Using Causal Analysis to Extract Rule Parameterization from Demonstrations
Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy
Learning models of user behaviour is an important problem that is broadly applicable across many application domains requiring human-robot interaction. In this work, we show that i…
E-HBA: Using Action Policies for Expert Advice and Agent Typification
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
Past research has studied two approaches to utilise predefined policy sets in repeated interactions: as experts, to dictate our own actions, and as types, to characterise the behav…
On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems
Stefano V. Albrecht, Subramanian Ramamoorthy
While many multiagent algorithms are designed for homogeneous systems (i.e. all agents are identical), there are important applications which require an agent to coordinate its act…
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract)
Stefano V. Albrecht, Subramanian Ramamoorthy
Dynamic Bayesian networks (DBNs) are a general model for stochastic processes with partially observed states. Belief filtering in DBNs is the task of inferring the belief state (i.…