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+---
+draft: false
+title: "Spectra: An Expressive STRIPS-Inspired AI Planner Based on Automated Reasoning"
+authors: [
+    "Brandon Rozek",
+    "Selmer Bringsjord"
+]
+date: 2024-05-222
+publish_date: "2024/05/22"
+conference: "KI - Künstliche Intelligenz"
+
+isbn: ""
+doi: "10.1007/s13218-024-00847-8"
+language: "English"
+
+pdf_url: "https://link.springer.com/article/10.1007/s13218-024-00847-8"
+abstract: "Research in automated planning traditionally focuses on model-based approaches that often sacrifice expressivity for computational efficiency. For artificial agents that operate in complex environments, however, frequently the agent needs to reason about the beliefs of other agents and be capable of handling uncertainty. We present Spectra, a STRIPS-inspired AI planner built atop automated reasoning. Our system is expressive, in that we allow for state spaces to be defined as arbitrary formulae. Spectra is also designed to be logic-agnostic, as long as an automated reasoner exists that can perform entailment and question-answering over it. Spectra can handle environments of unbounded uncertainty; and with certain non-classical logics, our system can create plans under epistemic beliefs. We highlight all of these features using the cognitive calculus DCC. Lastly, we discuss that under this framework, in order to fully plan under uncertainty, a defeasible (= non-monotonic) logic can be used in conjunction with our planner."
+---
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diff --git a/content/publications.md b/content/publications.md
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+++ b/content/publications.md
@@ -13,10 +13,10 @@ aliases:
 - Venue: Künstliche Intelligenz (KI), 2024
 - Paper to appear late 2024
 
-(Forthcoming) Spectra: An Expressive STRIPS-Inspired AI Planner Based on Automated Reasoning
+[Spectra: An Expressive STRIPS-Inspired AI Planner Based on Automated Reasoning](/paper/2405.01)
 - Authors: *Brandon Rozek* and Selmer Bringsjord
 - Venue: Künstliche Intelligenz (KI), 2024
-- Paper to appear late 2024
+- [Paper](https://link.springer.com/article/10.1007/s13218-024-00847-8) | [Paper](https://rdcu.be/dIJ7F)
 
 [Partially Observable Hierarchical Reinforcement Learning with AI Planning (Student Abstract)](/paper/2403.01)
 - Authors: *Brandon Rozek*, Junkyu Lee, Harsha Kokel, Michael Katz and Shirin Sohrabi