ssardina-core

Expecting the unexpected: Goal recognition for rational and irrational agents

Contemporary cost-based goal-recognition assumes rationality: that observed behaviour is more or less optimal. Probabilistic goal recognition systems, however, explicitly depend on some degree of sub-optimality to generate probability distributions. …

Flexible FOND Planning with Explicit Fairness Assumptions

We consider the problem of reaching a propositional goal condition in fully-observable non-deterministic (FOND) planning under a general class of fairness assumptions that are given explicitly. The fairness assumptions are of the form A/B and say …

Cost-Based Goal Recognition in Navigational Domains

Goal recognition is the problem of determining an agent's intent by observing her behaviour. Contemporary solutions for general task-planning relate the probability of a goal to the cost of reaching it. We adapt this approach to goal recognition in …

Fully Observable Non-deterministic Planning as Assumption-based Reactive Synthesis

We contribute to recent efforts in relating two approaches to automatic synthesis, namely, automated planning and discrete reactive synthesis. First, we develop a declarative characterization of the standard \"fairness\" assumption on environments in …

Agent Planning Programs

This work proposes a novel high-level paradigm, agent planning programs, for modeling agents behavior, which suitably mixes automated planning with agent-oriented programming. Agent planning programs are finite-state programs, possibly containing …

Improving Domain-Independent Intention Selection in BDI Systems

The Belief Desire Intention (BDI) agent paradigm provides a powerful basis for developing complex systems based on autonomous intelligent agents. These agents have, at any point in time, a set of intentions encoding the various tasks the agent is …

Automatic Behavior Composition Synthesis

The behavior composition problem amounts to realizing a virtual desired module (e.g., a surveillance agent system) by suitably coordinating (and re-purposing) the execution of a set of available modules (e.g., a video camera, vacuum cleaner, a robot, …

Qualitative Approximate Behavior Composition

The behavior composition problem involves automatically building a controller that is able to realize a desired, but unavailable, target system (e.g., a house surveillance) by suitably coordinating a set of available components (e.g., video cameras, …

A BDI Agent Programming Language with Failure Recovery, Declarative Goals, and Planning

Agents are an important technology that have the potential to take over contemporary methods for analysing, designing, and implementing complex software. The Belief-Desire-Intention (BDI) agent paradigm has proven to be one of the major approaches to …

IndiGolog: A High-Level Programming Language for Embedded Reasoning Agents

IndiGolog isa programming language for autonomous agents that sense their environment and do planning as they operate. Instead of classical planning, it supports high-level program execution. The programmer provides a high-level non-deterministic …