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PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance

arXiv:2606.06823v1 Announce Type: new Abstract: While deep learning has excelled in various domains, its application to sequential decision-making in finance remains challenging due to the low Signal-to-Noise Ratio (SNR) and non-stationarity of financial data. Leveraging the reasoning capabilities of Large Language Models (LLMs), we propose \textbf{PandaAI}, a closed-loop neuro-symbolic LLM agent with market regime modeling and constrained alpha generation, which bridges general LLM...

arXiv CS 2d ago

An Infectious Disease Spread Simulation Based on Large Language Model Decision Making

Announce Type: new Abstract: Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective public health interventions. Prior work has shown that large language models can simulate realistic human behaviour by generating agent decisions based on demographic prompts and situational context.

arXiv CS 5d ago

An Infectious Disease Spread Simulation Based on Large Language Model Decision Making

arXiv:2606.06360v2 Announce Type: replace Abstract: Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective public health interventions. Prior work has shown that large language models can simulate realistic human behaviour by generating agent decisions based on demographic prompts and situational context. We build on this foundation with a spatially grounded, agent-based simulation framework that...

arXiv CS 1d ago

A thalamus–brainstem attractor network drives history-biased decisions

Abstract Natural environments often change gradually, making it adaptive to bias decisions on the basis of the recent past — a phenomenon known as serial dependence1,2,3. Large-scale recordings during behaviour have identified that serial dependence is a common motif for decision-making, with neural representations of past experiences found throughout the brain4,5,6,7,8,9,10,11. However, it remains unclear whether this bias arises from dedicated neural circuits with history-specific...

Nature 20h ago

Architectural Evolution and Selection Framework for Database Systems in AI-Ready Data Platforms

arXiv:2606.08317v1 Announce Type: new Abstract: The rise of polyglot data management and AI-ready database architectures has created a complex design space across diverse database paradigms. However, architecture selection in modern enterprise environments continues to rely heavily on ad-hoc engineering intuition, with limited systematic frameworks to guide decision-making across heterogeneous database systems.

arXiv CS 1d ago

Computational Modeling of Human Adaptation in Urban Infrastructure Management under Extreme Conditions: A Case Study of Subway Flood Scenarios

arXiv:2606.06429v1 Announce Type: new Abstract: Decision-making in urban infrastructure management during extreme events relies heavily on human operators, yet current computational support systems often fail to account for non-monotonic human adaptation and latent psychological biases like overconfidence and defensive overcorrection. This study addresses this gap by integrating Instance-Based Learning Theory (IBLT) into the domain of civil engineering computing. We establish a computational...

arXiv CS 5d ago

The future of agriculture

The future of agriculture Lisa Lock Scientific Editor Andrew Zinin Lead Editor It's a mild early spring morning at the historic Cottonwood Field Station in western South Dakota, and a herd of 150 Angus steers are scheduled to move to a new pasture rotation. Moving cattle can be tricky and often requires some extra help, electrical fencing and quite a bit of time. But today, there are no extra ranchers, no gates swinging open and no temporary fences in place.

Phys.org 8d ago

Building user-driven climate adaptation products

Abstract Climate adaptation products have traditionally been developed using a supply-driven model reliant on available climate information, leading to usability gaps1,2,3,4. To better meet user needs, the climate services field has recognized a need to shift towards a demand-driven model emphasizing co-production, that is, user-driven, scientifically informed products created through shared knowledge practices1,2,3,4,5. However, co-production can be challenging, especially for researchers...

Nature 20h ago

Microsoft’s AI chief says superintelligence is near, but won’t take your job

Today I’m talking with Mustafa Suleyman, the CEO of Microsoft AI. And I’m actually going to keep today’s intro short — I’m working from my wife’s family farm this week, as you’ll see in the video, but also this is a real burner of an episode. We covered everything from Mustafa’s approach to training new models to his criticisms of Anthropic talking about Claude as though it is conscious.

The Verge 2d ago

How I Get Free Traffic from ChatGPT in 2025 (AIO vs SEO)

Three weeks ago, I tested something that completely changed how I think about organic traffic. I opened ChatGPT and asked a simple question: "What's the best course on building SaaS with WordPress?" The answer that appeared stopped me cold.

TechCrunch 188d ago