Today's large language models excel at pattern recall yet falter on long-range planning, self-critique, context loss, and the tendency of maximum-likelihood training to reward popularity over quality. MACI offers a promising route to AGI by orchestrating specialized LLM agents through explicit protocols rather than enlarging a single model. Several modules remedy complementary weaknesses: adversarial-collaborative debate surfaces hidden assumptions; critical-reading rubrics filter incoherent arguments; information-theoretic signals steer dialogue quantitatively; transactional memory enables reliable long-horizon execution; and a dual-agent ethical court adjudicates outputs. Crucially, MACI also modulates linguistic behavior, tuning each agent's contentiousness and emotional tone, so the collective explores ideas from contrasting, affect-aware perspectives before converging.

Fourteen aphorisms distill the framework's philosophy, including "Intelligence emerges from regulated collaboration, not isolated brilliance" and "Exploration must remain in tension with exploitation." Across healthcare diagnosis, investment support, scheduling, supply-chain management, and news-bias mitigation, MACI ensembles deliver significant improvements in reasoning depth, planning horizon, and reliability compared with similar-sized single models. By uniting structured debate, information-theoretic coordination, persistent memory, affect-aware discourse, and deliberative ethics, MACI demonstrates that rigorously validated multi-agent collaboration provides a practical, interpretable path toward robust general intelligence.

Edward Y. Chang is a computer scientist, academic, and author. He is an adjunct professor of Computer Science at Stanford University, and visiting chair professor of Bioinformatics and Medical Engineering at Asia University, since 2019.

Chang is the author of seven books, including Unlocking the Wisdom of Large Language Models (2024), Multi-LLM Agent Collaborative Intelligence：The Path to Artificial General Intelligence (2024), Foundations of Large-Scale Multimedia Information Management and Retrieval, Big Data Analytics for Large-Scale Multimedia Search, Journey of the Mind (poetry), Nomadic Eternity (poetry), and the Mandarin translation of Erwin Schrödinger's What is Life? Mind and Matter. His research interests span consciousness modeling, generative artificial intelligence, and health care, for which he has received numerous awards such as the Google Innovation Award, XPRIZE Award, and the Presidential Award of Taiwan for his work containing the COVID-19 outbreak. He is also a fellow of ACM Association for Computing Machinery and fellow of IEEE Institute of Electrical and Electronics Engineers for his contributions to scalable machine learning and healthcare.

Education
Chang completed his Master of Science in Industrial Engineering and Operations Research at the University of California, Berkeley before pursuing further studies at Stanford University. He received his Master of Science in Computer Science in 1994 and Ph.D. in Electrical Engineering in 1999 both from Stanford University, where he was advised by Hector Garcia-Molina. Beyond his technical education, he enrolled in more than ten courses in philosophy and literature, an intellectual breadth reflected in his publications.

Academia
Chang started his academic career at the University of California, Santa Barbara where he served as an Assistant, Associate, and eventually Full Professor of Electrical & Computer Engineering from 1999 to 2006. Between 2012 and 2015, he was appointed as an adjunct professor in Computer & Information Science at Hong Kong University of Science and Technology (HKUST), Hong Kong. This was followed by an appointment as a visiting professor at the Future Reality center in the EECS department of University of California, Berkeley from 2017 to 2020. Since 2019, he has been holding appointments as the adjunct professor of Computer Science at Stanford University[1] and Visiting Chair Professor of Bioinformatics and Medical Engineering at Asia University.[

Industry
Chang was Director of Research at Google from 2006 to 2012. During this time, he led research and development initiatives in several areas, including Web-scale image annotation (2008), data-centric scalable machine learning (2005-2012), recommendation systems, indoor localization, and Google QA.From 2012 to 2020, he served as the President of HTC Healthcare. Chang served as the Chief NLP Advisor at SmartNews, a Tokyo-based company, between 2019 and 2022, where he contributed in developing interactive news.