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A logic-based explanation generation framework for classical and hybrid planning problems
In human-aware planning systems, a planning agent might need to explain its plan to a
human user when that plan appears to be non-feasible or sub-optimal. A popular approach …
human user when that plan appears to be non-feasible or sub-optimal. A popular approach …
[КНИГА][B] Explainable human-AI interaction: A planning perspective
From its inception, artificial intelligence (AI) has had a rather ambivalent relationship with
humans—swinging between their augmentation and replacement. Now, as AI technologies …
humans—swinging between their augmentation and replacement. Now, as AI technologies …
Beyond one-shot explanations: a systematic literature review of dialogue-based xAI approaches
In the last decade, there has been increasing interest in allowing users to understand how
the predictions of machine-learned models come about, thus increasing transparency and …
the predictions of machine-learned models come about, thus increasing transparency and …
Subgoal-based explanations for unreliable intelligent decision support systems
Intelligent decision support (IDS) systems leverage artificial intelligence techniques to
generate recommendations that guide human users through the decision making phases of …
generate recommendations that guide human users through the decision making phases of …
Vizxp: A visualization framework for conveying explanations to users in model reconciliation problems
Advancements in explanation generation for automated planning algorithms have moved us
a step closer towards realizing the full potential of human-AI collaboration in real-world …
a step closer towards realizing the full potential of human-AI collaboration in real-world …
Human-AI symbiosis: A survey of current approaches
Z Zahedi, S Kambhampati - ar** AI agents capable of effectively
interacting and teaming with humans. While each of these works try to tackle a problem quite …
interacting and teaming with humans. While each of these works try to tackle a problem quite …
Explain it as simple as possible, but no simpler–Explanation via model simplification for addressing inferential gap
One of the core challenges of explaining decisions made by modern AI systems is the need
to address the potential gap in the inferential capabilities of the system generating the …
to address the potential gap in the inferential capabilities of the system generating the …
On Generating Monolithic and Model Reconciling Explanations in Probabilistic Scenarios
SL Vasileiou, W Yeoh, A Previti, TC Son - ar** and deploying complex AI systems that can potentially transform everyday life …