YES
We show the termination of the TRS R:

  app(f(),app(app(cons(),nil()),y)) -> y
  app(f(),app(app(cons(),app(f(),app(app(cons(),nil()),y))),z)) -> app(app(app(copy(),n()),y),z)
  app(app(app(copy(),|0|()),y),z) -> app(f(),z)
  app(app(app(copy(),app(s(),x)),y),z) -> app(app(app(copy(),x),y),app(app(cons(),app(f(),y)),z))
  app(app(map(),|fun|),nil()) -> nil()
  app(app(map(),|fun|),app(app(cons(),x),xs)) -> app(app(cons(),app(|fun|,x)),app(app(map(),|fun|),xs))
  app(app(filter(),|fun|),nil()) -> nil()
  app(app(filter(),|fun|),app(app(cons(),x),xs)) -> app(app(app(app(filter2(),app(|fun|,x)),|fun|),x),xs)
  app(app(app(app(filter2(),true()),|fun|),x),xs) -> app(app(cons(),x),app(app(filter(),|fun|),xs))
  app(app(app(app(filter2(),false()),|fun|),x),xs) -> app(app(filter(),|fun|),xs)

Instead we prove termination of the uncurried system:

  app(cons_0(),y) -> cons_1(y)
  app(cons_1(x1),y) -> cons_2(x1,y)
  app(copy_0(),y) -> copy_1(y)
  app(copy_1(x1),y) -> copy_2(x1,y)
  app(copy_2(x1,x2),y) -> copy_3(x1,x2,y)
  app(f_0(),y) -> f_1(y)
  app(filter_0(),y) -> filter_1(y)
  app(filter_1(x1),y) -> filter_2(x1,y)
  app(filter2_0(),y) -> filter2_1(y)
  app(filter2_1(x1),y) -> filter2_2(x1,y)
  app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
  app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
  app(map_0(),y) -> map_1(y)
  app(map_1(x1),y) -> map_2(x1,y)
  app(s_0(),y) -> s_1(y)
  f_1(cons_2(nil_0(),y)) -> y
  f_1(cons_2(f_1(cons_2(nil_0(),y)),z)) -> copy_3(n_0(),y,z)
  copy_3(|0|_0(),y,z) -> f_1(z)
  copy_3(s_1(x),y,z) -> copy_3(x,y,cons_2(f_1(y),z))
  map_2(|fun|,nil_0()) -> nil_0()
  map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs))
  filter_2(|fun|,nil_0()) -> nil_0()
  filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs)
  filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs))
  filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs)


-- SCC decomposition.

Consider the dependency pair problem (P, R), where P consists of

p1: app#(copy_2(x1,x2),y) -> copy_3#(x1,x2,y)
p2: app#(f_0(),y) -> f_1#(y)
p3: app#(filter_1(x1),y) -> filter_2#(x1,y)
p4: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y)
p5: app#(map_1(x1),y) -> map_2#(x1,y)
p6: f_1#(cons_2(f_1(cons_2(nil_0(),y)),z)) -> copy_3#(n_0(),y,z)
p7: copy_3#(|0|_0(),y,z) -> f_1#(z)
p8: copy_3#(s_1(x),y,z) -> copy_3#(x,y,cons_2(f_1(y),z))
p9: copy_3#(s_1(x),y,z) -> f_1#(y)
p10: map_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x)
p11: map_2#(|fun|,cons_2(x,xs)) -> map_2#(|fun|,xs)
p12: filter_2#(|fun|,cons_2(x,xs)) -> filter2_4#(app(|fun|,x),|fun|,x,xs)
p13: filter_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x)
p14: filter2_4#(true_0(),|fun|,x,xs) -> filter_2#(|fun|,xs)
p15: filter2_4#(false_0(),|fun|,x,xs) -> filter_2#(|fun|,xs)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(copy_0(),y) -> copy_1(y)
r4: app(copy_1(x1),y) -> copy_2(x1,y)
r5: app(copy_2(x1,x2),y) -> copy_3(x1,x2,y)
r6: app(f_0(),y) -> f_1(y)
r7: app(filter_0(),y) -> filter_1(y)
r8: app(filter_1(x1),y) -> filter_2(x1,y)
r9: app(filter2_0(),y) -> filter2_1(y)
r10: app(filter2_1(x1),y) -> filter2_2(x1,y)
r11: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r12: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r13: app(map_0(),y) -> map_1(y)
r14: app(map_1(x1),y) -> map_2(x1,y)
r15: app(s_0(),y) -> s_1(y)
r16: f_1(cons_2(nil_0(),y)) -> y
r17: f_1(cons_2(f_1(cons_2(nil_0(),y)),z)) -> copy_3(n_0(),y,z)
r18: copy_3(|0|_0(),y,z) -> f_1(z)
r19: copy_3(s_1(x),y,z) -> copy_3(x,y,cons_2(f_1(y),z))
r20: map_2(|fun|,nil_0()) -> nil_0()
r21: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs))
r22: filter_2(|fun|,nil_0()) -> nil_0()
r23: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs)
r24: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs))
r25: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs)

The estimated dependency graph contains the following SCCs:

  {p3, p4, p5, p10, p11, p12, p13, p14, p15}
  {p8}


-- Reduction pair.

Consider the dependency pair problem (P, R), where P consists of

p1: map_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x)
p2: app#(map_1(x1),y) -> map_2#(x1,y)
p3: map_2#(|fun|,cons_2(x,xs)) -> map_2#(|fun|,xs)
p4: app#(filter2_3(x1,x2,x3),y) -> filter2_4#(x1,x2,x3,y)
p5: filter2_4#(false_0(),|fun|,x,xs) -> filter_2#(|fun|,xs)
p6: filter_2#(|fun|,cons_2(x,xs)) -> app#(|fun|,x)
p7: app#(filter_1(x1),y) -> filter_2#(x1,y)
p8: filter_2#(|fun|,cons_2(x,xs)) -> filter2_4#(app(|fun|,x),|fun|,x,xs)
p9: filter2_4#(true_0(),|fun|,x,xs) -> filter_2#(|fun|,xs)

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(copy_0(),y) -> copy_1(y)
r4: app(copy_1(x1),y) -> copy_2(x1,y)
r5: app(copy_2(x1,x2),y) -> copy_3(x1,x2,y)
r6: app(f_0(),y) -> f_1(y)
r7: app(filter_0(),y) -> filter_1(y)
r8: app(filter_1(x1),y) -> filter_2(x1,y)
r9: app(filter2_0(),y) -> filter2_1(y)
r10: app(filter2_1(x1),y) -> filter2_2(x1,y)
r11: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r12: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r13: app(map_0(),y) -> map_1(y)
r14: app(map_1(x1),y) -> map_2(x1,y)
r15: app(s_0(),y) -> s_1(y)
r16: f_1(cons_2(nil_0(),y)) -> y
r17: f_1(cons_2(f_1(cons_2(nil_0(),y)),z)) -> copy_3(n_0(),y,z)
r18: copy_3(|0|_0(),y,z) -> f_1(z)
r19: copy_3(s_1(x),y,z) -> copy_3(x,y,cons_2(f_1(y),z))
r20: map_2(|fun|,nil_0()) -> nil_0()
r21: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs))
r22: filter_2(|fun|,nil_0()) -> nil_0()
r23: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs)
r24: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs))
r25: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs)

The set of usable rules consists of

  r3, r11, r20, r22

Take the reduction pair:

  generalized weighted path order (>=MG, >G)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          map_2#_A(x1,x2) = x2 + 6
          cons_2_A(x1,x2) = x1 + x2 + 9
          app#_A(x1,x2) = x2 + 14
          map_1_A(x1) = x1 + 7
          filter2_3_A(x1,x2,x3) = x1 + x2 + 9
          filter2_4#_A(x1,x2,x3,x4) = x4 + 13
          false_0_A() = 13
          filter_2#_A(x1,x2) = x2 + 12
          filter_1_A(x1) = x1 + 2
          app_A(x1,x2) = x1 + 20
          true_0_A() = 11
          copy_0_A() = 1
          copy_1_A(x1) = 2
          filter2_2_A(x1,x2) = x1 + x2 + 23
          map_2_A(x1,x2) = x2 + 8
          nil_0_A() = 1
          filter_2_A(x1,x2) = x1 + x2 + 1
  
    base order 2:
  
      marked-algebra reduction triple (>=A, >=A!, >A!):
      
        max/plus interpretation on natural numbers:
        
          map_2#_A(x1,x2) = max{1, x1 - 97, x2 - 19}
          cons_2_A(x1,x2) = max{x1 + 18, x2}
          app#_A(x1,x2) = max{1, x1 - 101, x2 - 19}
          map_1_A(x1) = max{7, x1 + 4}
          filter2_3_A(x1,x2,x3) = max{x1 - 59, x2 + 4, x3 + 100}
          filter2_4#_A(x1,x2,x3,x4) = max{1, x2 - 100, x3 - 1, x4 - 19}
          false_0_A = 0
          filter_2#_A(x1,x2) = max{1, x1 - 100, x2 - 19}
          filter_1_A(x1) = max{4, x1 + 1}
          app_A(x1,x2) = max{x1 - 29, x2 + 100}
          true_0_A = 102
          copy_0_A = 28
          copy_1_A(x1) = max{8, x1 - 97}
          filter2_2_A(x1,x2) = max{x1 - 30, x2 + 33}
          map_2_A(x1,x2) = max{x1 - 11, x2 + 100}
          nil_0_A = 91
          filter_2_A(x1,x2) = max{90, x1 - 103, x2 + 1}
          map_2#!_A(x1,x2) = max{5, x1 - 8}
          cons_2!_A(x1,x2) = max{92, x1 + 2, x2 + 4}
          app#!_A(x1,x2) = max{93, x1 + 88, x2 + 92}
          map_1!_A(x1) = max{107, x1 - 7}
          filter2_3!_A(x1,x2,x3) = max{109, x1 - 102, x3 - 1}
          filter2_4#!_A(x1,x2,x3,x4) = max{91, x3 + 1, x4 + 3}
          false_0!_A = 97
          filter_2#!_A(x1,x2) = max{91, x2 + 3}
          filter_1!_A(x1) = max{107, x1 - 6}
          app!_A(x1,x2) = max{x1 - 5, x2 + 106}
          true_0!_A = 95
          copy_0!_A = 1
          copy_1!_A(x1) = max{105, x1 - 1}
          filter2_2!_A(x1,x2) = max{108, x1 - 5, x2 + 107}
          map_2!_A(x1,x2) = max{x1 - 6, x2 + 105}
          nil_0!_A = 114
          filter_2!_A(x1,x2) = max{96, x1 - 5, x2 + 89}
  
    partial status:
  
      pi(map_2#) = []
      pi(cons_2) = []
      pi(app#) = [2]
      pi(map_1) = [1]
      pi(filter2_3) = [1, 2]
      pi(filter2_4#) = []
      pi(false_0) = []
      pi(filter_2#) = []
      pi(filter_1) = [1]
      pi(app) = [1]
      pi(true_0) = []
      pi(copy_0) = []
      pi(copy_1) = []
      pi(filter2_2) = [1, 2]
      pi(map_2) = []
      pi(nil_0) = []
      pi(filter_2) = [1]

The following rules are removed:

  p1, p2, p3, p4, p5, p6, p7, p8, p9

Then no dependency pair remains.

-- Reduction pair.

Consider the dependency pair problem (P, R), where P consists of

p1: copy_3#(s_1(x),y,z) -> copy_3#(x,y,cons_2(f_1(y),z))

and R consists of:

r1: app(cons_0(),y) -> cons_1(y)
r2: app(cons_1(x1),y) -> cons_2(x1,y)
r3: app(copy_0(),y) -> copy_1(y)
r4: app(copy_1(x1),y) -> copy_2(x1,y)
r5: app(copy_2(x1,x2),y) -> copy_3(x1,x2,y)
r6: app(f_0(),y) -> f_1(y)
r7: app(filter_0(),y) -> filter_1(y)
r8: app(filter_1(x1),y) -> filter_2(x1,y)
r9: app(filter2_0(),y) -> filter2_1(y)
r10: app(filter2_1(x1),y) -> filter2_2(x1,y)
r11: app(filter2_2(x1,x2),y) -> filter2_3(x1,x2,y)
r12: app(filter2_3(x1,x2,x3),y) -> filter2_4(x1,x2,x3,y)
r13: app(map_0(),y) -> map_1(y)
r14: app(map_1(x1),y) -> map_2(x1,y)
r15: app(s_0(),y) -> s_1(y)
r16: f_1(cons_2(nil_0(),y)) -> y
r17: f_1(cons_2(f_1(cons_2(nil_0(),y)),z)) -> copy_3(n_0(),y,z)
r18: copy_3(|0|_0(),y,z) -> f_1(z)
r19: copy_3(s_1(x),y,z) -> copy_3(x,y,cons_2(f_1(y),z))
r20: map_2(|fun|,nil_0()) -> nil_0()
r21: map_2(|fun|,cons_2(x,xs)) -> cons_2(app(|fun|,x),map_2(|fun|,xs))
r22: filter_2(|fun|,nil_0()) -> nil_0()
r23: filter_2(|fun|,cons_2(x,xs)) -> filter2_4(app(|fun|,x),|fun|,x,xs)
r24: filter2_4(true_0(),|fun|,x,xs) -> cons_2(x,filter_2(|fun|,xs))
r25: filter2_4(false_0(),|fun|,x,xs) -> filter_2(|fun|,xs)

The set of usable rules consists of

  r16, r17

Take the reduction pair:

  generalized weighted path order (>=MG, >G)
  
    base order 1:
  
      matrix interpretation with standard point-wise order:
      
        carrier: N^1
        order: standard order
        interpretations:
          copy_3#_A(x1,x2,x3) = x1 + x3 + 2
          s_1_A(x1) = x1 + 5
          cons_2_A(x1,x2) = x2 + 4
          f_1_A(x1) = x1 + 8
          nil_0_A() = 2
          copy_3_A(x1,x2,x3) = x1 + x3 + 2
          n_0_A() = 1
  
    base order 2:
  
      marked-algebra reduction triple (>=A, >=A!, >A!):
      
        max/plus interpretation on natural numbers:
        
          copy_3#_A(x1,x2,x3) = max{0, x1 - 57, x2 - 57, x3 - 4}
          s_1_A(x1) = max{4, x1 + 1}
          cons_2_A(x1,x2) = max{3, x1 - 72, x2 - 18}
          f_1_A(x1) = max{24, x1 + 19}
          nil_0_A = 54
          copy_3_A(x1,x2,x3) = max{23, x1 - 57, x2 - 58, x3 - 4}
          n_0_A = 29
          copy_3#!_A(x1,x2,x3) = max{1, x1 - 2}
          s_1!_A(x1) = max{4, x1 - 1}
          cons_2!_A(x1,x2) = max{3, x1 - 57, x2 - 55}
          f_1!_A(x1) = 12
          nil_0!_A = 7
          copy_3!_A(x1,x2,x3) = max{12, x1 - 33, x2 - 39, x3 - 56}
          n_0!_A = 1
  
    partial status:
  
      pi(copy_3#) = []
      pi(s_1) = [1]
      pi(cons_2) = []
      pi(f_1) = []
      pi(nil_0) = []
      pi(copy_3) = []
      pi(n_0) = []

The following rules are removed:

  p1

Then no dependency pair remains.