Distributed and Parallel Computing
4 papers, newest first.
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Multi-Agent Daily Planning System (MADPS): A GAIA-Based Architecture for Dynamic Scheduling
Shuvam Agarwala, Ali Mohammadi RuzbahaniThis document outlines the GAIA methodology design for a single-user Multi-Agent Daily Planning System (MADPS) engineered to generate, adapt, and personalize daily schedules. The architecture consists of three core autonomous components: the User Profile Agent (UPA), the Task Management Agent (TMA), and the Planning & Adaptation Agent (PAA). MADPS is designed to maximize priority satisfaction under constraints, minimize re-planning latency and schedule churn during task disruptions, and personalize schedules by learning user energy curves and preference weights. To support these objectives, the system employs FIPA-style interaction protocols and a dual-strategy PAA workflow, utilizing rapid, greedy local repairs for minor schedule disruptions and Genetic Algorithm (GA)-driven global optimization for system-wide impacts. Proposed schedules are evaluated using a comprehensive fitness function that carefully weights priority satisfaction, energy alignment, transition minimization, and hard constraint penalties to ensure feasible and highly optimized daily plans.
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Smart Contracts as Autonomous Agents: Engineering a Decentralized Naming Infrastructure on the Polygon Blockchain
Shuvam Agarwala, Ali Mohammadi RuzbahaniWhile traditional multi-agent system (MAS) frameworks such as JADE and SPADE rely on distributed computing environments and asynchronous message passing, "Report-2.pdf" presents a novel paradigm: deploying blockchain smart contracts as fully autonomous agents. This detailed development document chronicles the implementation of the University of Calgary Name Service (UCNS) on the Polygon network, systematically translating abstract GAIA architectural designs into executable Solidity code. The specification provides a comprehensive engineering blueprint, encompassing detailed use case specifications, UML class and sequence diagrams modeling trustless inter-agent protocols, and explicit entity-relationship data structures. By detailing Web3 frontend integration, rigorous testing strategies, and mainnet deployment procedures, this report demonstrates how transaction-based coordination effectively replaces centralized platform mediation. The resulting implementation validates the application of agent-oriented software engineering principles to build secure, immutable, and production-ready decentralized applications
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Architecting Decentralized Identity: An Agent-Oriented Naming Infrastructure on the Polygon Blockchain
Shuvam Agarwala, Ali Mohammadi RuzbahaniTraditional blockchain naming systems typically rely on monolithic smart contracts that couple logic tightly, limiting component isolation, independent upgradeability, and clear behavioral reasoning. As detailed in "Report-1A-System-Specification.pdf", the University of Calgary Name Service (UCNS) overcomes these limitations through a fully decentralized, agent-based naming infrastructure deployed on the Polygon network. By applying agent-oriented software engineering principles to a Web3 environment, UCNS decomposes system architecture into three autonomous smart contract entities: a Registry Agent, a Resolver Agent, and a Pricing Agent. These independent agents operate without centralized control, coordinating seamlessly through structured message-passing to execute domain registration, lifecycle ownership management, dynamic pricing, and address resolution. This modular separation of concerns ensures verifiable ownership, tamper-proof state maintenance, and transparent on-chain computation while establishing a robust foundation for multi-agent systems in decentralized applications. Ultimately, this specification demonstrates the viability of specialized autonomous agents in replacing monolithic paradigms for practical, production-grade blockchain identity management.
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Decentralizing Cybersecurity across Artificial Intelligence, Internet of Things, Blockchain, Machine Learning, and Agentic AI: A Systematic Literature Review
Rezvan AbouzadehCybersecurity was built around a perimeter, a trusted central server, and a human analyst who reads the alerts. None of the three holds up well in deployments where billions of constrained devices generate data at the edge, models are trained across organizational borders, ledgers record who did what, and autonomous software agents act at machine speed on behalf of people. This article reviews how decentralization is being used to respond to that shift. We code and synthesize 216 studies, 94 of them drawn from one research programme on federated, blockchain-based, and autonomous defence and 122 from the wider literature on mechanisms, attacks, and standards, across five technology families: the Internet of Things, machine learning, federated and other decentralized learning, blockchain, and agentic artificial intelligence. Four findings stand out. Decentralized learning is the most mature of the strands and now has a credible answer to poisoning and inference threats, though at a cost in complexity that few papers measure. Blockchains contribute auditability and identity more reliably than they contribute detection. Agentic AI is the least settled strand, with evidence of attack running well ahead of evidence of defence. And very few studies combine more than two families, so the integrated architectures the field keeps proposing are mostly untested. We distil three reusable algorithms and a layered reference architecture, and we close with a research agenda built around accountability, evaluation, and post-quantum readiness.