# Review of Intelligent Methods and Their Potential Use towards a Smart Grid Negotiation Framework
## 2 Methodology  
In this survey, a total of 24 studies were examined, published from 1994 to 2023. The selected studies were chosen because of their potential applicability to the Energy Transaction context in SG. Seven of them focus on e-commerce and cloud services applications where negotiations take place, seven focus on energy transactions and allocation of sources in electricity networks and buildings, three refer to general applications without specific examples, six present examples covering a wide range of applications from negotiation in politics to car market negotiation, and one reviews the application of PSO variants in DSM applications. The majority of them introduce FS while some refer to MA, such as GA, PSO, and Bat Algorithm (BA). A summary is presented in Table 1. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Year** & **Title/Author(s)** & \multicolumn{2}{c}{**Commodity/Application**} & **Method** \\ \hline
1994 & “Fuzzy Constraint Satisfaction” & Addressing problems where not all given constraints need to be satisfied, by introducing soft constraints which are adequate. & Introducing soft constraints and Fuzzy constraints to Constraint Satisfaction Problem (CSP) for which various tuples adjust the defined constraints to a different level. The heuristic search solving approaches to CSP can be performed by branch-and-bound search. \\ \hline
2001 & “A genetic agent-based negotiation ([PERSON], [PERSON] and [PERSON]) & e-commerce & GA-agent Automated Negotiation System (ANS). GA negotiation agents adapt to the user’s preferences by dynamically modifying their mutation rate. \\ \hline
2002 & “Using similarity criteria to make issue trade-offs in automated negotiations” ([PERSON], [PERSON] and [PERSON]) & General-Car dealer negotiation as an example & Linear algorithm which operates by leveraging Fuzzy similarity to estimate the preference framework of the negotiating party, subsequently employing a hill-climbing technique to navigate the spectrum of possible trade-offs and locate the most probable acceptable option. \\ \hline
2005 & “Buyer-Supplier Negotiation by Fuzzy Logic Based Agents” ([PERSON], [PERSON] and [PERSON]) & e-marketplaces & The agent’s negotiation tactics presented as Fuzzy rules also acquired through learning processes, enabling agents to infer from past offers and approximate the opponent’s preference structure. \\ \hline
2006 & “Intelligent agents for e-marketplace: Negotiation with issue trade-offs by Fuzzy inference systems” ([PERSON], [PERSON] and [PERSON]) & e-marketplaces & The agents employ tactics, explicitly formulating trade-offs as Fuzzy Inference System (FIS), which are then utilized to generate new offers in each round of negotiation. \\ \hline
2012 & “Negotiation Agent with Adaptive Attitude Bidding Strategy for Facilitating Energy Exchanges between Smart Building and Utility Grid” ([PERSON] and [PERSON]) & Smart and green buildings energy exchange & The negotiation agent, employing an Adaptive Attitude Bidding Strategy (AABS), explores different attitudes when determining bids. The negotiation model has been specifically crafted with the premise of bounded rationality rather than perfect rationality in mind. \\ \hline
2013 & “A single-issue negotiation model for agents bargaining in dynamic electronic markets” ([PERSON] and [PERSON]) & e-commerce & The desire-based negotiation model facilitates adaptive negotiation behaviors in e-markets by taking into account both the e-market’s conditions and the agent’s preferences. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of reviewed publications.