goal recognition and design

In goal recognition problems, the goal is to identify the goal of an observed agent as quickly as possible before they reach their goal. This problem can be applied to a number of applications ranging from software personal assistants and robots that anticipate the needs of humans; intelligent tutoring systems that recognize sources of confusion or misunderstanding in students through their interactions with the system; and security applications that recognize terrorists plans.

In goal recognition design problems, the objective is to identify the best ways to modify the underlying environment of the agents in such a way that they are forced to reveal their goals as early as possible. This problem is typically applicable in the same goal recognition applications as long as the underlying environment can be modified. For example, in intelligent tutoring systems, it is possible to modify the sequence or type of questions asked so that students’ misunderstanding can be identified sooner. Similarly, in security applications, it may be possible to block some paths so that an attacker’s plan can be recognized earlier. To learn more, please see our tutorial on goal recognition design, which we gave at ICAPS 2019. Slides available here.

Our current research is on both the algorithmic back-end, where the goal is to enrich the models so as to better capture more realistic problem characteristics and develop efficient algorithms to solve them, as well as the user interface front-end, where the goal is to develop visualization interfaces that allow our methods to be adapted to specific applications and evaluated with human users.


Improving Client Experience Through Goal Recognition and Explainable Assistance in Adaptive Systems.
J.P. Morgan Chase Bank (2022 – 2023).

Integrated Computational and Cognitive Workflows for Improved Security and Usability.
Boeing (2019).

CAREER: Decentralized Constraint-based Optimization for Multi-Agent Planning and Coordination.
National Science Foundation (2016 – 2021).

selected publications

    1. AAAI
      Stochastic Goal Recognition Design Problems with Suboptimal Agents
      Christabel Wayllace, and William Yeoh
      In AAAI Conference on Artificial Intelligence, 2022
      1. ECAI
        Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design
        Christabel Wayllace, Sarah Keren, Avigdor Gal, and 3 more authors
        In European Conference on Artificial Intelligence, 2020
          1. IJCAI
            New Metrics and Algorithms for Stochastic Goal Recognition Design Problems
            Christabel Wayllace, Ping Hou, and William Yeoh
            In International Joint Conference on Artificial Intelligence, 2017
          2. GameSec
            Game-Theoretic Goal Recognition Models with Applications to Security Domains
            Samuel Ang, Hau Chan, Albert Xin Jiang, and 1 more author
            In International Conference on Decision and Game Theory for Security, 2017
          1. IJCAI
            Goal Recognition Design with Stochastic Agent Action Outcomes
            Christabel Wayllace, Ping Hou, William Yeoh, and 1 more author
            In International Joint Conference on Artificial Intelligence, 2016