From 0fd4fb0c088ba081e25eb1e40e1f6eec004abbf6 Mon Sep 17 00:00:00 2001 From: Brandon Rozek Date: Fri, 1 May 2026 11:35:55 -0400 Subject: [PATCH 1/2] Updated publications list --- content/paper/2603.01.md | 22 ++++++++++++++++++++++ content/publications.md | 4 ++-- 2 files changed, 24 insertions(+), 2 deletions(-) create mode 100644 content/paper/2603.01.md diff --git a/content/paper/2603.01.md b/content/paper/2603.01.md new file mode 100644 index 0000000..1804081 --- /dev/null +++ b/content/paper/2603.01.md @@ -0,0 +1,22 @@ +--- +draft: false +title: "Filtering Goals of Necessity-Optimal Agents in Qualitative Possibilistic Recognition via Planning" +authors: [ + "Brandon Rozek", + "Selmer Bringsjord" +] +date: 2026-03-05 +publish_date: "2026/03/05" +conference: "International Conference on Agents and Artificial Intelligence" + + +isbn: "" +doi: "10.5220/0014347900004052" +volume: 4 +firstpage: 2997 +lastpage: 2008 +language: "English" + +pdf_url: "https://www.scitepress.org/Papers/2026/143479/143479.pdf" +abstract: "Rationally inferring the goal of an agent from observations of their actions is challenging. In the goal-recognition-as-planning literature, it is often assumed that the initial state of the environment is known. However, actors and observers do not always operate with complete knowledge. Instead, agents may be working with little information regarding the uncertainty of the environment. In this light, we revisit goal recognition in the context of qualitative possibilistic planning (QPP). Agents in this setting do not know the exact probability of an event occurring but are able to determine whether one event is more likely than another. More specifically, agents describe the uncertainty regarding the initial state and the outcome of actions qualitatively. We show that for rational actors, the observer should not filter goals solely based on necessity thresholds and instead propose a technique that takes into account whether the actor followed a necessity-optimal plan. Using our novel compilation CQPR, we find those necessity-optimal plans that additionally satisfy the observed action sequence by casting the overall problem as a QPP problem. Our formal results and experiments show that this approach is sound and may narrow down the potential goals that a necessity-optimal agent is pursuing." +--- \ No newline at end of file diff --git a/content/publications.md b/content/publications.md index 0f04ab4..cd6656e 100644 --- a/content/publications.md +++ b/content/publications.md @@ -8,10 +8,10 @@ aliases: ## Publications -Filtering Goals of Necessity-Optimal Agents in Qualitative Possibilistic Recognition via Planning +[Filtering Goals of Necessity-Optimal Agents in Qualitative Possibilistic Recognition via Planning](/paper/2603.01) - Authors: *Brandon Rozek* and Selmer Bringsjord - Venue: International Conference on Agents and Artificial Intelligence, 2026. - +-[Paper](https://doi.org/10.5220/0014347900004052) | [Paper](https://www.scitepress.org/Papers/2026/143479/143479.pdf) [VSPursuer: A Tool for Finding Matrices Witnessing the Variable Sharing Property](/paper/2602.01) - Authors: *Brandon Rozek* and Andrew Tedder From db60366724c9e7362ec50e76ca9ede2c6a275377 Mon Sep 17 00:00:00 2001 From: Brandon Rozek Date: Fri, 1 May 2026 13:14:39 -0400 Subject: [PATCH 2/2] Updated TA page --- content/ta/_index.md | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/content/ta/_index.md b/content/ta/_index.md index 2963f0c..939c63f 100644 --- a/content/ta/_index.md +++ b/content/ta/_index.md @@ -3,8 +3,19 @@ title: Teaching Assistant description: My work as a teaching assistent --- +## Spring 2026 +I was a TA for Dr. Selmer Bringsjord's COGS-4962 Introduction to Logic-Based AI. + +Office Hours: Thursday 1000-1200 + +## Fall 2025 + +I was a TA for Dr. Ana Milanova's CSCI-4430 Programming Langauges. + +Office Hours: Thursday 1400-1800 + ## Spring 2022 -I am a TA for Dr. Konstantin Kuzmin's CSCI 2600 Principles of Software +I was a TA for Dr. Konstantin Kuzmin's CSCI 2600 Principles of Software. Recitation: Wednesday 1200-1250 / 1300-1350