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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.07977 |
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| _version_ | 1866929624227774464 |
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| author | Dernbach, Stefan Michel, Alejandro Agarwal, Khushbu Brissette, Christopher Gupta, Geetika Choudhury, Sutanay |
| author_facet | Dernbach, Stefan Michel, Alejandro Agarwal, Khushbu Brissette, Christopher Gupta, Geetika Choudhury, Sutanay |
| contents | This paper introduces lateral thinking to implement System-2 reasoning capabilities in AI systems, focusing on anticipatory and causal reasoning under uncertainty. We present a framework for systematic generation and modeling of lateral thinking queries and evaluation datasets. We introduce Streaming Agentic Lateral Thinking (SALT), a multi-agent framework designed to process complex, low-specificity queries in streaming data environments. SALT implements lateral thinking-inspired System-2 reasoning through a dynamic communication structure between specialized agents. Our key insight is that lateral information flow across long-distance agent interactions, combined with fine-grained belief management, yields richer information contexts and enhanced reasoning. Preliminary quantitative and qualitative evaluations indicate SALT's potential to outperform single-agent systems in handling complex lateral reasoning tasks in a streaming environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_07977 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Thinking Fast and Laterally: Multi-Agentic Approach for Reasoning about Uncertain Emerging Events Dernbach, Stefan Michel, Alejandro Agarwal, Khushbu Brissette, Christopher Gupta, Geetika Choudhury, Sutanay Artificial Intelligence This paper introduces lateral thinking to implement System-2 reasoning capabilities in AI systems, focusing on anticipatory and causal reasoning under uncertainty. We present a framework for systematic generation and modeling of lateral thinking queries and evaluation datasets. We introduce Streaming Agentic Lateral Thinking (SALT), a multi-agent framework designed to process complex, low-specificity queries in streaming data environments. SALT implements lateral thinking-inspired System-2 reasoning through a dynamic communication structure between specialized agents. Our key insight is that lateral information flow across long-distance agent interactions, combined with fine-grained belief management, yields richer information contexts and enhanced reasoning. Preliminary quantitative and qualitative evaluations indicate SALT's potential to outperform single-agent systems in handling complex lateral reasoning tasks in a streaming environment. |
| title | Thinking Fast and Laterally: Multi-Agentic Approach for Reasoning about Uncertain Emerging Events |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2412.07977 |