Related papers: Revisiting Actor Programming in C++
\EcoLab{} is an agent based modeling system for C++ programmers, strongly influenced by the design of Swarm. This paper is just a brief outline of \EcoLab's features, more details can be found in other published articles, documentation and…
We introduce the simulation tool SABCEMM (Simulator for Agent-Based Computational Economic Market Models) for agent-based computational economic market (ABCEM) models. Our simulation tool is implemented in C++ and we can easily run ABCEM…
ActorScript(TM) is a general purpose programming language for implementing discretionary, adaptive concurrency that manages resources and demand. It is differentiated from previous languages by the following: - Universality *** Ability to…
Brand and Zafiropulo's notion of Communicating Finite-State Machines (CFSMs) provides a succinct and powerful model of message-passing concurrency, based around channels. However, a major variant of message-passing concurrency is not…
Recent advances in large language models (LLMs) have opened new avenues for applying multi-agent systems in very large-scale simulations. However, there remain several challenges when conducting multi-agent simulations with existing…
Currently, agent-based simulation frameworks force the user to choose between simulations involving a large number of agents (at the expense of limited agent reasoning capability) or simulations including agents with increased reasoning…
Despite the importance of sparse matrices in numerous fields of science, software implementations remain difficult to use for non-expert users, generally requiring the understanding of underlying details of the chosen sparse matrix storage…
Data sharing is central to a wide variety of applications such as fraud detection, ad matching, and research. The lack of data sharing abstractions makes the solution to each data sharing problem bespoke and cost-intensive, hampering value…
Collective Adaptive Intelligence (CAI) represent a transformative approach in embodied AI, wherein numerous autonomous agents collaborate, adapt, and self-organize to navigate complex, dynamic environments. By enabling systems to…
The Polymorphic Combinatorial Framework (PCF) leverages Large Language Models (LLMs) and mathematical frameworks to guide the meta-prompt enabled design of solution spaces and adaptive AI agents for complex, dynamic environments. Unlike…
Hybrid quantum-high performance computing (Q-HPC) workflows are emerging as a key strategy for running quantum applications at scale in current noisy intermediate-scale quantum (NISQ) devices. These workflows must operate seamlessly across…
Distributed in-network programs are increasingly deployed in data centers for their performance benefits, but shifting application logic to switches also enlarges the failure domain. Ensuring their correctness before deployment is thus…
Agent-based models have emerged as a promising paradigm for addressing ever increasing complexity of information systems. In its initial days in the 1990s when object-oriented modeling was at its peak, an agent was treated as a special kind…
In the artificial intelligence space, as we transition from isolated large language models to autonomous agents capable of complex reasoning and tool use. While foundational architectures and local context management protocols have been…
Recent demand for distributed software had led to a surge in popularity in actor-based frameworks. However, even with the stylized message passing model of actors, writing correct distributed software is still difficult. We present our work…
Programming models for distributed and heterogeneous machines are rapidly growing in popularity to meet the demands of modern workloads. Task and actor models are common choices that offer different trade-offs between development…
Bioscientists frequently seek to visualize the biological systems they have empirically characterized and reported in the literature. Realizing such visualizations requires biological structure modeling, an inherently complex process that…
Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such…
The ongoing convergence of HPC and cloud computing presents a fundamental challenge: HPC applications, designed for static and homogeneous supercomputers, are ill-suited for the dynamic, heterogeneous, and volatile nature of the cloud.…
Artificial intelligence (AI) is increasingly deployed in real-time and energy-constrained environments, driving demand for hardware platforms that can deliver high performance and power efficiency. While central processing units (CPUs) and…