Automated Negotiation for Supply Chain Management
Industrial Partner: NEC Corporation
NEC https://www.nec.com, founded in 1899, is now particularly addressing thedevelopment of solutions for society that will help resolve many issues the world isfacing and which will engender the creation of a brighter and more prosperous society.
Through co-creation initiatives with many stakeholders, including customers, business
partners, private individuals, government agencies, and international institutions, weare actively devising new business models to create social value by harnessing ourextensive information and communication technology (ICT) assets.
Industrial Mentor
Yasser Mohammad, Ph.D. NEC Corporation

Background
Negotiation is one of the most commonly used methods for reaching agreements inhuman society. With increased automation of business and industrial processes in thepast decades, interest in automating the negotiation process between AIs is growing
both in the industry and academia [1]. For example, an automated agent representing aconsumer (buyer) may negotiate price, quantity and delivery date with another representing
supplier (seller). Each agent is trying to maximize the profit of the firm it represents whileconsidering long-term relationships as well. By taking advantage of the computational power
and rationality of AI in this case, the buyer and seller may be able to reach agreements thatare better for both than what could be achieved through human negotiations. AutomatedNegotiation is the research field concerned with designing protocols and strategies forreaching agreements between self-interested agents that have their own preferences
over possible outcomes of the negotiation process.

Automated Negotiation research has a long history. Earliest approaches to AutomatedNegotiation relied on game-theoretic arguments to achieve theoretical guarantees in
simple situation (e.g. known preferences of all players)[6]. Most of this work wasgeared at understanding the negotiation process as an economic activity that underlies
agreements in modern society. Recently, interest has shifted towards building practicalapplications of automated negotiation technologies in several fields including supply
chain management, transportation, energy among many others.
Supply Chain Management (SCM) is one of the most important industrial activities
without which production cannot proceed. The goal of SCM is to make sure all required
supplies are available when needed where they are needed at an appropriate cost. Inpractice, SCM is done through concurrent closed negotiations between suppliers andconsumers, which leads in several instances to inefficiencies in transactions (i.e. money

left on the table). Automating the whole or a part of the SCM negotiation process canimprove the efficiency of business activities and industrial production significantly.
Automated Negotiation in SCM is not only an important industrial application but itprovides a testbed for advanced research on the edge of automated negotiation
including concurrent negotiations [2] and negotiation under uncertainty.
NEC has been engaged for several years in research and development activities related
to the application of automated negotiation to supply chain management among otherfields. One example is the NEC-AIST AI Cooperative Research Laboratory. Recently, NEC— with its partners — started a company for commercialization of the results of thisresearch activity and transferring it to real world application (The BIRD Initiative).
Moreover, NEC is working with international partners to standardize the automatednegotiation process to allow seamless interaction between multiple providers throughthe eNegotiation under the UNECE organization.
The growing interest in automated negotiation by academia is shown by theestablishment of the Automated Negotiating Agents Competition (ANAC) since 2010.
The competition is conducted every year as part of one of the top AI conferences (IJCAI,AAMAS). A special league about automated negotiation in SCM has been organized aspart of ANAC since 2019 (SCML)[4]. Our team is taking the lead in organizing SCML in
cooperation with researchers from MIT, Brown University, and Tokyo University ofAgriculture and Technology.

Project and Expectation
The project is expected to design, build and evaluate negotiation strategies to optimize
supply chain management in a business like simulation environment. The strategies areexpected to advance the state of the art by providing better performance than recent
winners of SCML. Moreover, analysis of existing strategies and their interactions using
rigorous game-theoretic approaches can occupy part of the project. Students should
also demonstrate the benefits and shortcomings of their strategy in the context of thesimulation environment provided by NEC.
Students need not know any details about automated negotiation or supply chain
management at the start of the project. They can learn these topics during the program.
Development will be conducted using Python so experience in using the Python
scientific stack will be a great time-saver.
The Platform
The platform used in this project is a community-driven, NEC supported open source
library developed for automated negotiation in general called NegMAS [3] with over
250,000 downloads.
NegMAS is a python library for developing autonomous negotiation agents embedded
in simulation environments. The name negmas stands for either NEGotiation

MultiAgent System or NEGotiations Managed by Agent Simulations (your pick). The
main goal of NegMAS is to advance the state-of-the-art in situated simultaneousnegotiations. Nevertheless, it also can (and was used) in modeling simpler bilateral andmultilateral negotiations, preference elicitation, etc.
It is the same platform used for the SCML competition. The source code of the platform
is available on GitHub and detailed documentation is also available. Online tutorials andother resources will be made available to students during the project.
The Competition
As discussed earlier, the project will lead to the development of negotiation strategies
for supply chain management. The strategies generated will be compatible with theSCML allowing students to submit their own agents to the competition in 2024. Details
bout the competition for 2023 can be found in its official website:
https://scml.cs.brown.edu.

Requirements
Programming skills (mainly in Python). Knowledge of reinforcement learning and gametheory is an advantage.

References
1.

Tim Baarslag, Michael Kaisers, Enrico Gerding, Catholijn M Jonker, and JonathanGratch. 2017. When will negotiation agents be able to represent us? The challenges
and opportunities for autonomous negotiators.

2.

Yasser Mohammad and Shinji Nakadai. 2022. Concurrent negotiations with global
utility functions. In Proceedings of the 21st international conference on autonomous
agents and multiagent systems, 1947–1949.

3.

Yasser Mohammad, Shinji Nakadai, and Amy Greenwald. 2021. NegMAS: A platform
for automated negotiations. In PRIMA 2020: Principles and practice of multi-agent
systems: 23rd international conference, nagoya, japan, november 18–20, 2020,proceedings 23, 343–351.

4.

Yasser Mohammad, Enrique Areyan Viqueira, Nahum Alvarez Ayerza, Amy
Greenwald, Shinji Nakadai, and Satoshi Morinaga. 2019. Supply chain management
world. In PRIMA 2019: Principles and practice of multi-agent systems, 153–169.

5.

John F Nash Jr. 1950. The bargaining problem. Econometrica: Journal of the
Econometric Society: 155–162.

6.

Ariel Rubinstein. 1982. Perfect equilibrium in a bargaining model. Econometrica:
Journal of the Econometric Society: 97–109.