linear form. One well known example of this class of games is the differentiated-product Cournot oligopoly with linear inverse demand and constant marginal cost with payoff function defined as [@BKA10]:$$U_{i}(x_{i},\mathbf{x}_{-i};\delta ,A_{\mathcal{G}})=x_{i}\left(
a-b(x_{i}+2\delta \sum_{j=1}^{n}a_{ij}x_{j})\right) -dx_{i},
\label{Game Payoffs}$$where $d$ is the constant marginal cost, and $x_{i}$ represents the amount produced by agent $i$ in the oligopoly. Here, the inverse demand for agent $i
$ is given by $P_{i}(x_{i},\mathbf{x}_{-i};\delta ,A_{\mathcal{G}%
})=a-b(x_{i}+2\delta \sum_{j=1}^{n}a_{ij}x_{j})$. One can prove that the best response function for this type of games yield the form [@BKA10]:$$f_{i}(\mathbf{x},\delta ,A_{\mathcal{G}})=\max (0,\bar{x}_{i}-\delta
\sum_{j=1}^{n}a_{ij}x_{j}),  \label{Best Reply Function}$$where $\bar{x}_{i}$ is the action that agent $i$ would take in isolation, i.e., $\bar{x}_{i}\in \arg \max_{x_{i}}U_{i}(x_{i},\mathbf{x}_{-i};\delta
,A_{\mathcal{G}})$ with $a_{ij}=0$,  for all $j$. Without loss of generality, one can normalize $\bar{x}_{i}\equiv 1$ for all $i$, so that $%
f_{i}(\mathbf{x})\in \lbrack 0,1]$. Then, a Nash equilibrium for this game is a vector $\mathbf{x}\in \lbrack 0,1]^{n}$ that satisfies $x_{i}=f_{i}(%
\mathbf{x},\delta ,A_{\mathcal{G}})$, for all agents $i\in \mathcal{N}$, simultaneously. In what follows, we briefly describe a strategy to compute the complete set of Nash equilibria for $\delta \in \lbrack 0,1]$.

Complete Set of Nash Equilibria
-------------------------------

Using the best response function in (\[Best Reply Function\]), one can determine the entire set of equilibria by 