5 Useful Docker Containers for Agentic Developers - KDnuggets
5 Useful Docker Containers for Agentic Developers KDnuggets
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Rashomon Memory: Towards Argumentation-Driven Retrieval for Multi-Perspective Agent Memory
arXiv:2604.03588v1 Announce Type: new Abstract: AI agents operating over extended time horizons accumulate experiences that serve multiple concurrent goals, and must often maintain conflicting interpretations of the same events. A concession during a client negotiation encodes as a ``trust-building investment'' for one strategic goal and a ``contractual liability'' for another. Current memory architectures assume a single correct encoding, or at best support multiple views over unified storage. We propose Rashomon Memory: an architecture where parallel goal-conditioned agents encode experiences according to their priorities and negotiate at query time through argumentation. Each perspective maintains its own ontology and knowledge graph. At retrieval, perspectives propose interpretations,
Personality Requires Struggle: Three Regimes of the Baldwin Effect in Neuroevolved Chess Agents
arXiv:2604.03565v1 Announce Type: new Abstract: Can lifetime learning expand behavioral diversity over evolutionary time, rather than collapsing it? Prior theory predicts that plasticity reduces variance by buffering organisms against environmental noise. We test this in a competitive domain: chess agents with eight NEAT-evolved neural modules, Hebbian within-game plasticity, and a desirability-domain signal chain with imagination. Across 10~seeds per Hebbian condition, a variance crossover emerges: Hebbian ON starts with lower cross-seed variance than OFF, then surpasses it at generation~34. The crossover trend is monotonic (\r{ho} = 0.91, p 0.8) with interpretable signal chain configurations. Three regimes appear depending on opponent type: exploration (Hebbian ON, heterogeneous opponent
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Agentization of Digital Assets for the Agentic Web: Concepts, Techniques, and Benchmark
arXiv:2604.04226v1 Announce Type: new Abstract: Agentic Web, as a new paradigm that redefines the internet through autonomous, goal-driven interactions, plays an important role in group intelligence. As the foundational semantic primitives of the Agentic Web, digital assets encapsulate interactive web elements into agents, which expand the capacities and coverage of agents in agentic web. The lack of automated methodologies for agent generation limits the wider usage of digital assets and the advancement of the Agentic Web. In this paper, we first formalize these challenges by strictly defining the A2A-Agentization process, decomposing it into critical stages and identifying key technical hurdles on top of the A2A protocol. Based on this framework, we develop an Agentization Agent to agent
Discussion: AI & Machine Learning Category
Title: Beyond RAG: Why AI Agents Need a Self-Hosted 'Memory Hub' Most developers working with LLMs are hitting the same wall: context window limitations and the 'forgetting' problem in long-running agentic workflows. While Retrieval-Augmented Generation (RAG) helps, it often lacks the deep, historical context of a user's entire digital life. However, moving a user's entire history into a cloud-based vector DB raises massive privacy red flags. This is where the concept of a self-hosted 'Privacy Memory Hub' becomes vital. By using something like Nexus Memory, developers can create a bridge where an agent is granted 'just-in-time' context from a locally controlled source. This ensures that the agent stays smart over months, not just minutes, while the user maintains absolute sovereignty over
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